Large Language Models on Producthunt daily

gallery

Mon, 06 Apr 2026 16:25:40 +0800

google-ai-edge/gallery

Google AI Edge Gallery ✨

Explore, Experience, and Evaluate the Future of On-Device Generative AI with Google AI Edge.

AI Edge Gallery is the premier destination for running the world’s most powerful open-source Large Language Models (LLMs) on your mobile device. Experience high-performance Generative AI directly on your hardware—fully offline, private, and lightning-fast.

Now Featuring: Gemma 4

The latest version brings official support for the newly released Gemma 4 family. As the centerpiece of this release, Gemma 4 allows you to test the cutting edge of on-device AI. Experience advanced reasoning, logic, and creative capabilities without ever sending your data to a server.

Install the app today from Google Play	Install the app today from App Store

For users without Google Play access, install the apk from the latest release

App Preview

✨ Core Features

Agent Skills: Transform your LLM from a conversationalist into a proactive assistant. Use the Agent Skills tile to augment model capabilities with tools like Wikipedia for fact-grounding, interactive maps, and rich visual summary cards. You can even load modular skills from a URL or browse community contributions on GitHub Discussions.
AI Chat with Thinking Mode: Engage in fluid, multi-turn conversations and toggle the new Thinking Mode to peek “under the hood.” This feature allows you to see the model’s step-by-step reasoning process, which is perfect for understanding complex problem-solving. Note: Thinking Mode currently works with supported models, starting with the Gemma 4 family.
Ask Image: Use multimodal power to identify objects, solve visual puzzles, or get detailed descriptions using your device’s camera or photo gallery.
Audio Scribe: Transcribe and translate voice recordings into text in real-time using high-efficiency on-device language models.
Prompt Lab: A dedicated workspace to test different prompts and single-turn use cases with granular control over model parameters like temperature and top-k.
Mobile Actions: Unlock offline device controls and automated tasks powered entirely by a finetune of FuntionGemma 270m.
Tiny Garden: A fun, experimental mini-game that uses natural language to plant and harvest a virtual garden using a finetune of FunctionGemma 270m.
Model Management & Benchmark: Gallery is a flexible sandbox for a wide variety of open-source models. Easily download models from the list or load your own custom models. Manage your model library effortlessly and run benchmark tests to understand exactly how each model performs on your specific hardware.
100% On-Device Privacy: All model inferences happen directly on your device hardware. No internet is required, ensuring total privacy for your prompts, images, and sensitive data.

🏁 Get Started in Minutes!

Check OS Requirement: Android 12 and up, and iOS 17 and up.
Download the App:
- Install the app from Google Play or App Store.
- For users without Google Play access: install the apk from the latest release
Install & Explore: For detailed installation instructions (including for corporate devices) and a full user guide, head over to our Project Wiki!

🛠️ Technology Highlights

Google AI Edge: Core APIs and tools for on-device ML.
LiteRT: Lightweight runtime for optimized model execution.
Hugging Face Integration: For model discovery and download.

⌨️ Development

Check out the development notes for instructions about how to build the app locally.

🤝 Feedback

This is an experimental Beta release, and your input is crucial!

🐞 Found a bug? Report it here!
💡 Have an idea? Suggest a feature!

📄 License

Licensed under the Apache License, Version 2.0. See the LICENSE file for details.

🔗 Useful Links

generative-ai-for-beginners

Tue, 09 Sep 2025 15:28:49 +0800

microsoft/generative-ai-for-beginners

21 Lessons teaching everything you need to know to start building Generative AI applications

🌐 Multi-Language Support

Supported via GitHub Action (Automated & Always Up-to-Date)

Generative AI for Beginners (Version 3) - A Course

Learn the fundamentals of building Generative AI applications with our 21-lesson comprehensive course by Microsoft Cloud Advocates.

🌱 Getting Started

This course has 21 lessons. Each lesson covers its own topic so start wherever you like!

Lessons are labeled either “Learn” lessons explaining a Generative AI concept or “Build” lessons that explain a concept and code examples in both Python and TypeScript when possible.

For .NET Developers checkout Generative AI for Beginners (.NET Edition)!

Each lesson also includes a “Keep Learning” section with additional learning tools.

What You Need

To run the code of this course, you can use either:

Azure OpenAI Service - Lessons: “aoai-assignment”
GitHub Marketplace Model Catalog - Lessons: “githubmodels”
OpenAI API - Lessons: “oai-assignment”
Basic knowledge of Python or TypeScript is helpful - *For absolute beginners check out these Python and TypeScript courses
A GitHub account to fork this entire repo to your own GitHub account

We have created a Course Setup lesson to help you with setting up your development environment.

Don’t forget to star (🌟) this repo to find it easier later.

🧠 Ready to Deploy?

If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both Python and TypeScript.

🗣️ Meet Other Learners, Get Support

Join our official Azure AI Foundry Discord server to meet and network with other learners taking this course and get support.

Ask questions or share product feedback in our Azure AI Foundry Developer Forum on Github.

🚀 Building a Startup?

Visit Microsoft for Startups to find out how to get started building with Azure credits today.

🙏 Want to help?

Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request

📂 Each lesson includes:

A short video introduction to the topic
A written lesson located in the README
Python and TypeScript code samples supporting Azure OpenAI and OpenAI API
Links to extra resources to continue your learning

🗃️ Lessons

#	Lesson Link	Description	Video	Extra Learning
00	Course Setup	Learn: How to Setup Your Development Environment	Video Coming Soon	Learn More
01	Introduction to Generative AI and LLMs	Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work.	Video	Learn More
02	Exploring and comparing different LLMs	Learn: How to select the right model for your use case	Video	Learn More
03	Using Generative AI Responsibly	Learn: How to build Generative AI Applications responsibly	Video	Learn More
04	Understanding Prompt Engineering Fundamentals	Learn: Hands-on Prompt Engineering Best Practices	Video	Learn More
05	Creating Advanced Prompts	Learn: How to apply prompt engineering techniques that improve the outcome of your prompts.	Video	Learn More
06	Building Text Generation Applications	Build: A text generation app using Azure OpenAI / OpenAI API	Video	Learn More
07	Building Chat Applications	Build: Techniques for efficiently building and integrating chat applications.	Video	Learn More
08	Building Search Apps Vector Databases	Build: A search application that uses Embeddings to search for data.	Video	Learn More
09	Building Image Generation Applications	Build: An image generation application	Video	Learn More
10	Building Low Code AI Applications	Build: A Generative AI application using Low Code tools	Video	Learn More
11	Integrating External Applications with Function Calling	Build: What is function calling and its use cases for applications	Video	Learn More
12	Designing UX for AI Applications	Learn: How to apply UX design principles when developing Generative AI Applications	Video	Learn More
13	Securing Your Generative AI Applications	Learn: The threats and risks to AI systems and methods to secure these systems.	Video	Learn More
14	The Generative AI Application Lifecycle	Learn: The tools and metrics to manage the LLM Lifecycle and LLMOps	Video	Learn More
15	Retrieval Augmented Generation (RAG) and Vector Databases	Build: An application using a RAG Framework to retrieve embeddings from a Vector Databases	Video	Learn More
16	Open Source Models and Hugging Face	Build: An application using open source models available on Hugging Face	Video	Learn More
17	AI Agents	Build: An application using an AI Agent Framework	Video	Learn More
18	Fine-Tuning LLMs	Learn: The what, why and how of fine-tuning LLMs	Video	Learn More
19	Building with SLMs	Learn: The benefits of building with Small Language Models	Video Coming Soon	Learn More
20	Building with Mistral Models	Learn: The features and differences of the Mistral Family Models	Video Coming Soon	Learn More
21	Building with Meta Models	Learn: The features and differences of the Meta Family Models	Video Coming Soon	Learn More

🌟 Special thanks

Special thanks to John Aziz for creating all of the GitHub Actions and workflows

Bernhard Merkle for making key contributions to each lesson to improve the learner and code experience.

🎒 Other Courses

Our team produces other courses! Check out:

Hands-On-Large-Language-Models

Wed, 27 Aug 2025 15:29:45 +0800

HandsOnLLM/Hands-On-Large-Language-Models

# Hands-On Large Language Models

Welcome! In this repository you will find the code for all examples throughout the book Hands-On Large Language Models written by Jay Alammar and Maarten Grootendorst which we playfully dubbed:

"The Illustrated LLM Book"

Through the visually educational nature of this book and with almost 300 custom made figures, learn the practical tools and concepts you need to use Large Language Models today!

The book is available on:

We advise to run all examples through Google Colab for the easiest setup. Google Colab allows you to use a T4 GPU with 16GB of VRAM for free. All examples were mainly built and tested using Google Colab, so it should be the most stable platform. However, any other cloud provider should work.

Chapter	Notebook
Chapter 1: Introduction to Language Models
Chapter 2: Tokens and Embeddings
Chapter 3: Looking Inside Transformer LLMs
Chapter 4: Text Classification
Chapter 5: Text Clustering and Topic Modeling
Chapter 6: Prompt Engineering
Chapter 7: Advanced Text Generation Techniques and Tools
Chapter 8: Semantic Search and Retrieval-Augmented Generation
Chapter 9: Multimodal Large Language Models
Chapter 10: Creating Text Embedding Models
Chapter 11: Fine-tuning Representation Models for Classification
Chapter 12: Fine-tuning Generation Models

[!TIP] You can check the setup folder for a quick-start guide to install all packages locally and you can check the conda folder for a complete guide on how to setup your environment, including conda and PyTorch installation. Note that the depending on your OS, Python version, and dependencies your results might be slightly differ. However, they should this be similar to the examples in the book.

Reviews

“Jay and Maarten have continued their tradition of providing beautifully illustrated and insightful descriptions of complex topics in their new book. Bolstered with working code, timelines, and references to key papers, their book is a valuable resource for anyone looking to understand the main techniques behind how Large Language Models are built.”

Andrew Ng - founder of DeepLearning.AI

“This is an exceptional guide to the world of language models and their practical applications in industry. Its highly-visual coverage of generative, representational, and retrieval applications of language models empowers readers to quickly understand, use, and refine LLMs. Highly recommended!”

Nils Reimers - Director of Machine Learning at Cohere | creator of sentence-transformers

“I can’t think of another book that is more important to read right now. On every single page, I learned something that is critical to success in this era of language models.”

Josh Starmer - StatQuest

“If you’re looking to get up to speed in everything regarding LLMs, look no further! In this wonderful book, Jay and Maarten will take you from zero to expert in the history and latest advances in large language models. With very intuitive explanations, great real-life examples, clear illustrations, and comprehensive code labs, this book lifts the curtain on the complexities of transformer models, tokenizers, semantic search, RAG, and many other cutting-edge technologies. A must read for anyone interested in the latest AI technology!”

Luis Serrano, PhD - Founder and CEO of Serrano Academy

“Hands-On Large Language Models brings clarity and practical examples to cut through the hype of AI. It provides a wealth of great diagrams and visual aids to supplement the clear explanations. The worked examples and code make concrete what other books leave abstract. The book starts with simple introductory beginnings, and steadily builds in scope. By the final chapters, you will be fine-tuning and building your own large language models with confidence.”

Leland McInnes - Researcher at the Tutte Institute for Mathematics and Computing | creator of UMAP and HDBSCAN

Bonus content!

We attempted to put as much information into the book without it being overwhelming. However, even with a 400-page book there is still much to discover!

We continue to create more guides that compliment the book and go more in-depth into new and exciting topics:

A Visual Guide to Mamba	A Visual Guide to Quantization	The Illustrated Stable Diffusion

A Visual Guide to Mixture of Experts	A Visual Guide to Reasoning LLMs	The Illustrated DeepSeek-R1

Citation

Please consider citing the book if you consider it useful for your research:

@book{hands-on-llms-book,
  author       = {Jay Alammar and Maarten Grootendorst},
  title        = {Hands-On Large Language Models},
  publisher    = {O'Reilly},
  year         = {2024},
  isbn         = {978-1098150969},
  url          = {https://www.oreilly.com/library/view/hands-on-large-language/9781098150952/},
  github       = {https://github.com/HandsOnLLM/Hands-On-Large-Language-Models}
}

poml

Sun, 17 Aug 2025 15:27:32 +0800

microsoft/poml

POML: Prompt Orchestration Markup Language

POML (Prompt Orchestration Markup Language) is a novel markup language designed to bring structure, maintainability, and versatility to advanced prompt engineering for Large Language Models (LLMs). It addresses common challenges in prompt development, such as lack of structure, complex data integration, format sensitivity, and inadequate tooling. POML provides a systematic way to organize prompt components, integrate diverse data types seamlessly, and manage presentation variations, empowering developers to create more sophisticated and reliable LLM applications.

Demo Video

Key Features

Structured Prompting Markup: Employs an HTML-like syntax with semantic components such as <role>, <task>, and <example> to encourage modular design, enhancing prompt readability, reusability, and maintainability.
Comprehensive Data Handling: Incorporates specialized data components (e.g., <document>, <table>, <img>) that seamlessly embed or reference external data sources like text files, spreadsheets, and images, with customizable formatting options.
Decoupled Presentation Styling: Features a CSS-like styling system that separates content from presentation. This allows developers to modify styling (e.g., verbosity, syntax format) via <stylesheet> definitions or inline attributes without altering core prompt logic, mitigating LLM format sensitivity.
Integrated Templating Engine: Includes a built-in templating engine with support for variables ({{ }}), loops (for), conditionals (if), and variable definitions (<let>) for dynamically generating complex, data-driven prompts.
Rich Development Toolkit:
- IDE Extension (Visual Studio Code): Provides essential development aids like syntax highlighting, context-aware auto-completion, hover documentation, real-time previews, inline diagnostics for error checking, and integrated interactive testing.
- Software Development Kits (SDKs): Offers SDKs for Node.js (JavaScript/TypeScript) and Python for seamless integration into various application workflows and popular LLM frameworks.

Quick Start

Here’s a very simple POML example. Please put it in a file named example.poml. Make sure it resides in the same directory as the photosynthesis_diagram.png image file.

<poml>
  <role>You are a patient teacher explaining concepts to a 10-year-old.</role>
  <task>Explain the concept of photosynthesis using the provided image as a reference.</task>

  <img src="photosynthesis_diagram.png" alt="Diagram of photosynthesis" />

  <output-format>
    Keep the explanation simple, engaging, and under 100 words.
    Start with "Hey there, future scientist!".
  </output-format>
</poml>

This example defines a role and task for the LLM, includes an image for context, and specifies the desired output format. With the POML toolkit, the prompt can be easily rendered with a flexible format, and tested with a vision LLM.

Installation

Visual Studio Code Extension

Install from Visual Studio Code Marketplace.

You can also install the extension manually by downloading the .vsix file from our GitHub releases page and installing it in VS Code via the Extensions view.

Before testing prompts with the POML toolkit, make sure you have configured your preferred LLM model, API key, and endpoint. If these are not set, prompt testing will not work.

To configure in Visual Studio Code:

Open the extension settings (open “Settings” and search for “POML”).
Set your model provider (e.g., OpenAI, Azure, Google), API key, and endpoint URL in the POML section.
Alternatively, you can add these settings directly to your settings.json file.

Node.js (via npm)

`1`	`npm install pomljs`

Python (via pip)

`1`	`pip install poml`

For development or local installation, you might use pip install -e . from a cloned repository.

Refer to the documentation for more details on installing the nightly build.

Documentation

For detailed information on POML syntax, components, styling, templating, SDKs, and the VS Code extension, please refer to our documentation.

Learn More

Watch our Demo Video on YouTube: POML Introduction & Demo
Join our Discord community: Connect with the team and other users on our Discord server.
Read the Research Paper (coming soon): For an in-depth understanding of POML’s design, implementation, and evaluation, check out our paper: Paper link TBD.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft’s Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies.

Responsible AI

This project has been evaluated and certified to comply with the Microsoft Responsible AI Standard. The team will continue to monitor and maintain the repository, addressing any severe issues, including potential harms, if they arise. For more details, refer to the Responsible AI Readme.

License

This project is licensed under the MIT License. See the LICENSE file for details.

gpt4all

Thu, 14 Aug 2025 15:31:32 +0800

nomic-ai/gpt4all

GPT4All

Now with support for DeepSeek R1 Distillations

Website • Documentation • Discord • YouTube Tutorial

GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.

No API calls or GPUs required - you can just download the application and get started.

Read about what's new in our blog.

Subscribe to the newsletter

https://github.com/nomic-ai/gpt4all/assets/70534565/513a0f15-4964-4109-89e4-4f9a9011f311

GPT4All is made possible by our compute partner Paperspace.

Download Links

— Windows Installer —

— Windows ARM Installer —

— macOS Installer —

— Ubuntu Installer —

The Windows and Linux builds require Intel Core i3 2nd Gen / AMD Bulldozer, or better.

The Windows ARM build supports Qualcomm Snapdragon and Microsoft SQ1/SQ2 processors.

The Linux build is x86-64 only (no ARM).

The macOS build requires Monterey 12.6 or newer. Best results with Apple Silicon M-series processors.

See the full System Requirements for more details.

Flathub (community maintained)

Install GPT4All Python

gpt4all gives you access to LLMs with our Python client around llama.cpp implementations.

Nomic contributes to open source software like llama.cpp to make LLMs accessible and efficient for all.

`1`	`pip install gpt4all`

from gpt4all import GPT4All
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf") # downloads / loads a 4.66GB LLM
with model.chat_session():
    print(model.generate("How can I run LLMs efficiently on my laptop?", max_tokens=1024))

Integrations

:parrot::link: Langchain :card_file_box: Weaviate Vector Database - module docs :telescope: OpenLIT (OTel-native Monitoring) - Docs

Release History

July 2nd, 2024: V3.0.0 Release
- Fresh redesign of the chat application UI
- Improved user workflow for LocalDocs
- Expanded access to more model architectures
October 19th, 2023: GGUF Support Launches with Support for:
- Mistral 7b base model, an updated model gallery on our website, several new local code models including Rift Coder v1.5
- Nomic Vulkan support for Q4_0 and Q4_1 quantizations in GGUF.
- Offline build support for running old versions of the GPT4All Local LLM Chat Client.
September 18th, 2023: Nomic Vulkan launches supporting local LLM inference on NVIDIA and AMD GPUs.
July 2023: Stable support for LocalDocs, a feature that allows you to privately and locally chat with your data.
June 28th, 2023: Docker-based API server launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.

Contributing

GPT4All welcomes contributions, involvement, and discussion from the open source community! Please see CONTRIBUTING.md and follow the issues, bug reports, and PR markdown templates.

Check project discord, with project owners, or through existing issues/PRs to avoid duplicate work. Please make sure to tag all of the above with relevant project identifiers or your contribution could potentially get lost. Example tags: backend, bindings, python-bindings, documentation, etc.

Citation

If you utilize this repository, models or data in a downstream project, please consider citing it with:

@misc{gpt4all,
  author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},
  title = {GPT4All: Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/nomic-ai/gpt4all}},
}

ollama

Fri, 08 Aug 2025 15:39:28 +0800

ollama/ollama

Ollama

Get up and running with large language models.

macOS

Download

Windows

Download

Linux

`1`	`curl -fsSL https://ollama.com/install.sh \| sh`

Manual install instructions

Docker

The official Ollama Docker image ollama/ollama is available on Docker Hub.

Libraries

Community

Quickstart

To run and chat with Gemma 3:

`1`	`ollama run gemma3`

Model library

Ollama supports a list of models available on ollama.com/library

Here are some example models that can be downloaded:

Model	Parameters	Size	Download
Gemma 3	1B	815MB	`ollama run gemma3:1b`
Gemma 3	4B	3.3GB	`ollama run gemma3`
Gemma 3	12B	8.1GB	`ollama run gemma3:12b`
Gemma 3	27B	17GB	`ollama run gemma3:27b`
QwQ	32B	20GB	`ollama run qwq`
DeepSeek-R1	7B	4.7GB	`ollama run deepseek-r1`
DeepSeek-R1	671B	404GB	`ollama run deepseek-r1:671b`
Llama 4	109B	67GB	`ollama run llama4:scout`
Llama 4	400B	245GB	`ollama run llama4:maverick`
Llama 3.3	70B	43GB	`ollama run llama3.3`
Llama 3.2	3B	2.0GB	`ollama run llama3.2`
Llama 3.2	1B	1.3GB	`ollama run llama3.2:1b`
Llama 3.2 Vision	11B	7.9GB	`ollama run llama3.2-vision`
Llama 3.2 Vision	90B	55GB	`ollama run llama3.2-vision:90b`
Llama 3.1	8B	4.7GB	`ollama run llama3.1`
Llama 3.1	405B	231GB	`ollama run llama3.1:405b`
Phi 4	14B	9.1GB	`ollama run phi4`
Phi 4 Mini	3.8B	2.5GB	`ollama run phi4-mini`
Mistral	7B	4.1GB	`ollama run mistral`
Moondream 2	1.4B	829MB	`ollama run moondream`
Neural Chat	7B	4.1GB	`ollama run neural-chat`
Starling	7B	4.1GB	`ollama run starling-lm`
Code Llama	7B	3.8GB	`ollama run codellama`
Llama 2 Uncensored	7B	3.8GB	`ollama run llama2-uncensored`
LLaVA	7B	4.5GB	`ollama run llava`
Granite-3.3	8B	4.9GB	`ollama run granite3.3`

[!NOTE] You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.

Customize a model

Import from GGUF

Ollama supports importing GGUF models in the Modelfile:

Create a file named Modelfile, with a FROM instruction with the local filepath to the model you want to import.
1

FROM ./vicuna-33b.Q4_0.gguf
Create the model in Ollama
1

ollama create example -f Modelfile
Run the model
1

ollama run example

Import from Safetensors

See the guide on importing models for more information.

Customize a prompt

Models from the Ollama library can be customized with a prompt. For example, to customize the llama3.2 model:

`1`	`ollama pull llama3.2`

Create a Modelfile:

FROM llama3.2

# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1

# set the system message
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""

Next, create and run the model:

ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.

For more information on working with a Modelfile, see the Modelfile documentation.

CLI Reference

Create a model

ollama create is used to create a model from a Modelfile.

`1`	`ollama create mymodel -f ./Modelfile`

Pull a model

`1`	`ollama pull llama3.2`

This command can also be used to update a local model. Only the diff will be pulled.

Remove a model

`1`	`ollama rm llama3.2`

Copy a model

`1`	`ollama cp llama3.2 my-model`

Multiline input

For multiline input, you can wrap text with """:

>>> """Hello,
... world!
... """
I'm a basic program that prints the famous "Hello, world!" message to the console.

Multimodal models

`1`	`ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"`

Output: The image features a yellow smiley face, which is likely the central focus of the picture.

Pass the prompt as an argument

`1`	`ollama run llama3.2 "Summarize this file: $(cat README.md)"`

Output: Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.

Show model information

`1`	`ollama show llama3.2`

List models on your computer

`1`	`ollama list`

List which models are currently loaded

`1`	`ollama ps`

Stop a model which is currently running

`1`	`ollama stop llama3.2`

Start Ollama

ollama serve is used when you want to start ollama without running the desktop application.

Building

See the developer guide

Running local builds

Next, start the server:

`1`	`./ollama serve`

Finally, in a separate shell, run a model:

`1`	`./ollama run llama3.2`

REST API

Ollama has a REST API for running and managing models.

Generate a response

curl http://localhost:11434/api/generate -d '{
  "model": "llama3.2",
  "prompt":"Why is the sky blue?"
}'

Chat with a model

curl http://localhost:11434/api/chat -d '{
  "model": "llama3.2",
  "messages": [
    { "role": "user", "content": "why is the sky blue?" }
  ]
}'

See the API documentation for all endpoints.

Community Integrations

Web & Desktop

Open WebUI
SwiftChat (macOS with ReactNative)
Enchanted (macOS native)
Hollama
Lollms-Webui
LibreChat
Bionic GPT
HTML UI
Saddle
TagSpaces (A platform for file-based apps, utilizing Ollama for the generation of tags and descriptions)
Chatbot UI
Chatbot UI v2
Typescript UI
Minimalistic React UI for Ollama Models
Ollamac
big-AGI
Cheshire Cat assistant framework
Amica
chatd
Ollama-SwiftUI
Dify.AI
MindMac
NextJS Web Interface for Ollama
Msty
Chatbox
WinForm Ollama Copilot
NextChat with Get Started Doc
Alpaca WebUI
OllamaGUI
OpenAOE
Odin Runes
LLM-X (Progressive Web App)
AnythingLLM (Docker + MacOs/Windows/Linux native app)
Ollama Basic Chat: Uses HyperDiv Reactive UI
Ollama-chats RPG
IntelliBar (AI-powered assistant for macOS)
Jirapt (Jira Integration to generate issues, tasks, epics)
ojira (Jira chrome plugin to easily generate descriptions for tasks)
QA-Pilot (Interactive chat tool that can leverage Ollama models for rapid understanding and navigation of GitHub code repositories)
ChatOllama (Open Source Chatbot based on Ollama with Knowledge Bases)
CRAG Ollama Chat (Simple Web Search with Corrective RAG)
RAGFlow (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
StreamDeploy (LLM Application Scaffold)
chat (chat web app for teams)
Lobe Chat with Integrating Doc
Ollama RAG Chatbot (Local Chat with multiple PDFs using Ollama and RAG)
BrainSoup (Flexible native client with RAG & multi-agent automation)
macai (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
RWKV-Runner (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
Ollama Grid Search (app to evaluate and compare models)
Olpaka (User-friendly Flutter Web App for Ollama)
Casibase (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support, and multiple large language models.)
OllamaSpring (Ollama Client for macOS)
LLocal.in (Easy to use Electron Desktop Client for Ollama)
Shinkai Desktop (Two click install Local AI using Ollama + Files + RAG)
AiLama (A Discord User App that allows you to interact with Ollama anywhere in Discord)
Ollama with Google Mesop (Mesop Chat Client implementation with Ollama)
R2R (Open-source RAG engine)
Ollama-Kis (A simple easy-to-use GUI with sample custom LLM for Drivers Education)
OpenGPA (Open-source offline-first Enterprise Agentic Application)
Painting Droid (Painting app with AI integrations)
Kerlig AI (AI writing assistant for macOS)
AI Studio
Sidellama (browser-based LLM client)
LLMStack (No-code multi-agent framework to build LLM agents and workflows)
BoltAI for Mac (AI Chat Client for Mac)
Harbor (Containerized LLM Toolkit with Ollama as default backend)
PyGPT (AI desktop assistant for Linux, Windows, and Mac)
Alpaca (An Ollama client application for Linux and macOS made with GTK4 and Adwaita)
AutoGPT (AutoGPT Ollama integration)
Go-CREW (Powerful Offline RAG in Golang)
PartCAD (CAD model generation with OpenSCAD and CadQuery)
Ollama4j Web UI - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j
PyOllaMx - macOS application capable of chatting with both Ollama and Apple MLX models.
Cline - Formerly known as Claude Dev is a VSCode extension for multi-file/whole-repo coding
Cherry Studio (Desktop client with Ollama support)
ConfiChat (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
Archyve (RAG-enabling document library)
crewAI with Mesop (Mesop Web Interface to run crewAI with Ollama)
Tkinter-based client (Python tkinter-based Client for Ollama)
LLMChat (Privacy focused, 100% local, intuitive all-in-one chat interface)
Local Multimodal AI Chat (Ollama-based LLM Chat with support for multiple features, including PDF RAG, voice chat, image-based interactions, and integration with OpenAI.)
ARGO (Locally download and run Ollama and Huggingface models with RAG and deep research on Mac/Windows/Linux)
OrionChat - OrionChat is a web interface for chatting with different AI providers
G1 (Prototype of using prompting strategies to improve the LLM’s reasoning through o1-like reasoning chains.)
Web management (Web management page)
Promptery (desktop client for Ollama.)
Ollama App (Modern and easy-to-use multi-platform client for Ollama)
chat-ollama (a React Native client for Ollama)
SpaceLlama (Firefox and Chrome extension to quickly summarize web pages with ollama in a sidebar)
YouLama (Webapp to quickly summarize any YouTube video, supporting Invidious as well)
DualMind (Experimental app allowing two models to talk to each other in the terminal or in a web interface)
ollamarama-matrix (Ollama chatbot for the Matrix chat protocol)
ollama-chat-app (Flutter-based chat app)
Perfect Memory AI (Productivity AI assists personalized by what you have seen on your screen, heard, and said in the meetings)
Hexabot (A conversational AI builder)
Reddit Rate (Search and Rate Reddit topics with a weighted summation)
OpenTalkGpt (Chrome Extension to manage open-source models supported by Ollama, create custom models, and chat with models from a user-friendly UI)
VT (A minimal multimodal AI chat app, with dynamic conversation routing. Supports local models via Ollama)
Nosia (Easy to install and use RAG platform based on Ollama)
Witsy (An AI Desktop application available for Mac/Windows/Linux)
Abbey (A configurable AI interface server with notebooks, document storage, and YouTube support)
Minima (RAG with on-premises or fully local workflow)
aidful-ollama-model-delete (User interface for simplified model cleanup)
Perplexica (An AI-powered search engine & an open-source alternative to Perplexity AI)
Ollama Chat WebUI for Docker (Support for local docker deployment, lightweight ollama webui)
AI Toolkit for Visual Studio Code (Microsoft-official VSCode extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.)
MinimalNextOllamaChat (Minimal Web UI for Chat and Model Control)
Chipper AI interface for tinkerers (Ollama, Haystack RAG, Python)
ChibiChat (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints)
LocalLLM (Minimal Web-App to run ollama models on it with a GUI)
Ollamazing (Web extension to run Ollama models)
OpenDeepResearcher-via-searxng (A Deep Research equivalent endpoint with Ollama support for running locally)
AntSK (Out-of-the-box & Adaptable RAG Chatbot)
MaxKB (Ready-to-use & flexible RAG Chatbot)
yla (Web interface to freely interact with your customized models)
LangBot (LLM-based instant messaging bots platform, with Agents, RAG features, supports multiple platforms)
1Panel (Web-based Linux Server Management Tool)
AstrBot (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
Reins (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
Flufy (A beautiful chat interface for interacting with Ollama’s API. Built with React, TypeScript, and Material-UI.)
Ellama (Friendly native app to chat with an Ollama instance)
screenpipe Build agents powered by your screen history
Ollamb (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the web demo.)
Writeopia (Text editor with integration with Ollama)
AppFlowy (AI collaborative workspace with Ollama, cross-platform and self-hostable)
Lumina (A lightweight, minimal React.js frontend for interacting with Ollama servers)
Tiny Notepad (A lightweight, notepad-like interface to chat with ollama available on PyPI)
macLlama (macOS native) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
GPTranslate (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
ollama launcher (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
ai-hub (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
Mayan EDMS (Open source document management system to organize, tag, search, and automate your files with powerful Ollama driven workflows.)

Cloud

Terminal

oterm
Ellama Emacs client
Emacs client
neollama UI client for interacting with models from within Neovim
gen.nvim
ollama.nvim
ollero.nvim
ollama-chat.nvim
ogpt.nvim
gptel Emacs client
Oatmeal
cmdh
ooo
shell-pilot(Interact with models via pure shell scripts on Linux or macOS)
tenere
llm-ollama for Datasette’s LLM CLI.
typechat-cli
ShellOracle
tlm
podman-ollama
gollama
ParLlama
Ollama eBook Summary
Ollama Mixture of Experts (MOE) in 50 lines of code
vim-intelligence-bridge Simple interaction of “Ollama” with the Vim editor
x-cmd ollama
bb7
SwollamaCLI bundled with the Swollama Swift package. Demo
aichat All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
PowershAI PowerShell module that brings AI to terminal on Windows, including support for Ollama
DeepShell Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
orbiton Configuration-free text editor and IDE with support for tab completion with Ollama.
orca-cli Ollama Registry CLI Application - Browse, pull, and download models from Ollama Registry in your terminal.
GGUF-to-Ollama - Importing GGUF to Ollama made easy (multiplatform)
AWS-Strands-With-Ollama - AWS Strands Agents with Ollama Examples
ollama-multirun - A bash shell script to run a single prompt against any or all of your locally installed ollama models, saving the output and performance statistics as easily navigable web pages. (Demo)
ollama-bash-toolshed - Bash scripts to chat with tool using models. Add new tools to your shed with ease. Runs on Ollama.

Apple Vision Pro

SwiftChat (Cross-platform AI chat app supporting Apple Vision Pro via “Designed for iPad”)
Enchanted

Database

pgai - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector)
- Get started guide
MindsDB (Connects Ollama models with nearly 200 data platforms and apps)
chromem-go with example
Kangaroo (AI-powered SQL client and admin tool for popular databases)

Package managers

Libraries

LangChain and LangChain.js with example
Firebase Genkit
crewAI
Yacana (User-friendly multi-agent framework for brainstorming and executing predetermined flows with built-in tool integration)
Spring AI with reference and example
LangChainGo with example
LangChain4j with example
LangChainRust with example
LangChain for .NET with example
LLPhant
LlamaIndex and LlamaIndexTS
LiteLLM
OllamaFarm for Go
OllamaSharp for .NET
Ollama for Ruby
Ollama-rs for Rust
Ollama-hpp for C++
Ollama4j for Java
ModelFusion Typescript Library
OllamaKit for Swift
Ollama for Dart
Ollama for Laravel
LangChainDart
Semantic Kernel - Python
Haystack
Elixir LangChain
Ollama for R - rollama
Ollama for R - ollama-r
Ollama-ex for Elixir
Ollama Connector for SAP ABAP
Testcontainers
Portkey
PromptingTools.jl with an example
LlamaScript
llm-axe (Python Toolkit for Building LLM Powered Apps)
Gollm
Gollama for Golang
Ollamaclient for Golang
High-level function abstraction in Go
Ollama PHP
Agents-Flex for Java with example
Parakeet is a GoLang library, made to simplify the development of small generative AI applications with Ollama.
Haverscript with examples
Ollama for Swift
Swollama for Swift with DocC
GoLamify
Ollama for Haskell
multi-llm-ts (A Typescript/JavaScript library allowing access to different LLM in a unified API)
LlmTornado (C# library providing a unified interface for major FOSS & Commercial inference APIs)
Ollama for Zig
Abso (OpenAI-compatible TypeScript SDK for any LLM provider)
Nichey is a Python package for generating custom wikis for your research topic
Ollama for D
OllamaPlusPlus (Very simple C++ library for Ollama)

Mobile

SwiftChat (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS, and iPad)
Enchanted
Maid
Ollama App (Modern and easy-to-use multi-platform client for Ollama)
ConfiChat (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
Ollama Android Chat (No need for Termux, start the Ollama service with one click on an Android device)
Reins (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)

Extensions & Plugins

Raycast extension
Discollama (Discord bot inside the Ollama discord channel)
Continue
Vibe (Transcribe and analyze meetings with Ollama)
Obsidian Ollama plugin
Logseq Ollama plugin
NotesOllama (Apple Notes Ollama plugin)
Dagger Chatbot
Discord AI Bot
Ollama Telegram Bot
Hass Ollama Conversation
Rivet plugin
Obsidian BMO Chatbot plugin
Cliobot (Telegram bot with Ollama support)
Copilot for Obsidian plugin
Obsidian Local GPT plugin
Open Interpreter
Llama Coder (Copilot alternative using Ollama)
Ollama Copilot (Proxy that allows you to use Ollama as a copilot like GitHub Copilot)
twinny (Copilot and Copilot chat alternative using Ollama)
Wingman-AI (Copilot code and chat alternative using Ollama and Hugging Face)
Page Assist (Chrome Extension)
Plasmoid Ollama Control (KDE Plasma extension that allows you to quickly manage/control Ollama model)
AI Telegram Bot (Telegram bot using Ollama in backend)
AI ST Completion (Sublime Text 4 AI assistant plugin with Ollama support)
Discord-Ollama Chat Bot (Generalized TypeScript Discord Bot w/ Tuning Documentation)
ChatGPTBox: All in one browser extension with Integrating Tutorial
Discord AI chat/moderation bot Chat/moderation bot written in python. Uses Ollama to create personalities.
Headless Ollama (Scripts to automatically install ollama client & models on any OS for apps that depend on ollama server)
Terraform AWS Ollama & Open WebUI (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front-end Open WebUI service.)
node-red-contrib-ollama
Local AI Helper (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.)
vnc-lm (Discord bot for messaging with LLMs through Ollama and LiteLLM. Seamlessly move between local and flagship models.)
LSP-AI (Open-source language server for AI-powered functionality)
QodeAssist (AI-powered coding assistant plugin for Qt Creator)
Obsidian Quiz Generator plugin
AI Summmary Helper plugin
TextCraft (Copilot in Word alternative using Ollama)
Alfred Ollama (Alfred Workflow)
TextLLaMA A Chrome Extension that helps you write emails, correct grammar, and translate into any language
Simple-Discord-AI
LLM Telegram Bot (telegram bot, primary for RP. Oobabooga-like buttons, A1111 API integration e.t.c)
mcp-llm (MCP Server to allow LLMs to call other LLMs)
SimpleOllamaUnity (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime)
UnityCodeLama (Unity Edtior tool to analyze scripts via Ollama)
NativeMind (Private, on-device AI Assistant, no cloud dependencies)
GMAI - Gradle Managed AI (Gradle plugin for automated Ollama lifecycle management during build phases)

Supported backends

llama.cpp project founded by Georgi Gerganov.

Observability

Opik is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native intergration to Ollama.
Lunary is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
OpenLIT is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
HoneyHive is an AI observability and evaluation platform for AI agents. Use HoneyHive to evaluate agent performance, interrogate failures, and monitor quality in production.
Langfuse is an open source LLM observability platform that enables teams to collaboratively monitor, evaluate and debug AI applications.
MLflow Tracing is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.

prompt-optimizer

Thu, 31 Jul 2025 15:34:38 +0800

linshenkx/prompt-optimizer

Prompt Optimizer (提示词优化器) 🚀

English | 中文

在线体验 | 快速开始 | 常见问题 | Chrome插件

开发文档 | Vercel部署指南 | MCP部署使用说明 | DeepWiki文档 | ZRead文档

📖 项目简介

Prompt Optimizer是一个强大的AI提示词优化工具，帮助你编写更好的AI提示词，提升AI输出质量。支持Web应用、桌面应用、Chrome插件和Docker部署四种使用方式。

🎥 功能演示

1. 角色扮演对话：激发小模型潜力

在追求成本效益的生产或注重隐私的本地化场景中，结构化的提示词能让小模型稳定地进入角色，提供沉浸式、高一致性的角色扮演体验，有效激发其潜力。

2. 知识图谱提取：保障生产环境的稳定性

在需要程序化处理的生产环境中，高质量的提示词能显著降低对模型智能程度的要求，使得更经济的小模型也能稳定输出可靠的指定格式。本工具旨在辅助开发者快速达到此目的，从而加速开发、保障稳定，实现降本增效。

3. 诗歌写作：辅助创意探索与需求定制

当面对一个强大的AI，我们的目标不只是得到一个“好”答案，而是得到一个“我们想要的”独特答案。本工具能帮助用户将一个模糊的灵感（如“写首诗”）细化为具体的需求（关于什么主题、何种意象、何种情感），辅助您探索、发掘并精确表达自己的创意，与AI共创独一无二的作品。

✨ 核心特性

🎯 智能优化：一键优化提示词，支持多轮迭代改进，提升AI回复准确度
📝 双模式优化：支持系统提示词优化和用户提示词优化，满足不同使用场景
🔄 对比测试：支持原始提示词和优化后提示词的实时对比，直观展示优化效果
🤖 多模型集成：支持OpenAI、Gemini、DeepSeek、智谱AI、SiliconFlow等主流AI模型
🔒 安全架构：纯客户端处理，数据直接与AI服务商交互，不经过中间服务器
📱 多端支持：同时提供Web应用、桌面应用、Chrome插件和Docker部署四种使用方式
🔐 访问控制：支持密码保护功能，保障部署安全
🧩 MCP协议支持：支持Model Context Protocol (MCP) 协议，可与Claude Desktop等MCP兼容应用集成

快速开始

1. 使用在线版本（推荐）

直接访问：https://prompt.always200.com

项目是纯前端项目，所有数据只存储在浏览器本地，不会上传至任何服务器，因此直接使用在线版本也是安全可靠的

2. Vercel部署

方式1：一键部署到自己的Vercel(方便，但后续无法自动更新)：

方式2: Fork项目后在Vercel中导入（推荐，但需参考部署文档进行手动设置）：

先Fork项目到自己的GitHub
然后在Vercel中导入该项目
可跟踪源项目更新，便于同步最新功能和修复
配置环境变量：
- ACCESS_PASSWORD：设置访问密码，启用访问限制
- VITE_OPENAI_API_KEY等：配置各AI服务商的API密钥

更多详细的部署步骤和注意事项，请查看：

Vercel部署指南

3. 下载桌面应用

从 GitHub Releases 下载最新版本。我们为各平台提供安装程序和压缩包两种格式。

安装程序 (推荐): 如 *.exe, *.dmg, *.AppImage 等。强烈推荐使用此方式，因为它支持自动更新。
压缩包: 如 *.zip。解压即用，但无法自动更新。

桌面应用核心优势:

✅ 无跨域限制：作为原生桌面应用，它能彻底摆脱浏览器跨域（CORS）问题的困扰。这意味着您可以直接连接任何AI服务提供商的API，包括本地部署的Ollama或有严格安全策略的商业API，获得最完整、最稳定的功能体验。
✅ 自动更新：通过安装程序（如 .exe, .dmg）安装的版本，能够自动检查并更新到最新版。
✅ 独立运行：无需依赖浏览器，提供更快的响应和更佳的性能。

4. 安装Chrome插件

从Chrome商店安装（由于审批较慢，可能不是最新的）：Chrome商店地址
点击图标即可打开提示词优化器

5. Docker部署

点击查看 Docker 部署命令

# 运行容器（默认配置）
docker run -d -p 8081:80 --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizer

# 运行容器（配置API密钥和访问密码）
docker run -d -p 8081:80 \
  -e VITE_OPENAI_API_KEY=your_key \
  -e ACCESS_USERNAME=your_username \  # 可选，默认为"admin"
  -e ACCESS_PASSWORD=your_password \  # 设置访问密码
  --restart unless-stopped \
  --name prompt-optimizer \
  linshen/prompt-optimizer

国内镜像: 如果Docker Hub访问较慢，可以将上述命令中的 linshen/prompt-optimizer 替换为 registry.cn-guangzhou.aliyuncs.com/prompt-optimizer/prompt-optimizer

6. Docker Compose部署

点击查看 Docker Compose 部署步骤

# 1. 克隆仓库
git clone https://github.com/linshenkx/prompt-optimizer.git
cd prompt-optimizer

# 2. 可选：创建.env文件配置API密钥和访问认证
cp env.local.example .env
# 编辑 .env 文件，填入实际的 API 密钥和配置

# 3. 启动服务
docker compose up -d

# 4. 查看日志
docker compose logs -f

# 5. 访问服务
Web 界面：http://localhost:8081
MCP 服务器：http://localhost:8081/mcp

你还可以直接编辑docker-compose.yml文件，自定义配置：

点击查看 docker-compose.yml 示例

services:
  prompt-optimizer:
    # 使用Docker Hub镜像
    image: linshen/prompt-optimizer:latest
    # 或使用阿里云镜像（国内用户推荐）
    # image: registry.cn-guangzhou.aliyuncs.com/prompt-optimizer/prompt-optimizer:latest
    container_name: prompt-optimizer
    restart: unless-stopped
    ports:
      - "8081:80"  # Web应用端口（包含MCP服务器，通过/mcp路径访问）
    environment:
      # API密钥配置
      - VITE_OPENAI_API_KEY=your_openai_key
      - VITE_GEMINI_API_KEY=your_gemini_key
      # 访问控制（可选）
      - ACCESS_USERNAME=admin
      - ACCESS_PASSWORD=your_password

7. MCP Server 使用说明

点击查看 MCP Server 使用说明

Prompt Optimizer 现在支持 Model Context Protocol (MCP) 协议，可以与 Claude Desktop 等支持 MCP 的 AI 应用集成。

当通过 Docker 运行时，MCP Server 会自动启动，并可通过 http://ip:port/mcp 访问。

环境变量配置

MCP Server 需要配置 API 密钥才能正常工作。主要的 MCP 专属配置：

1
2
3

# MCP 服务器配置
MCP_DEFAULT_MODEL_PROVIDER=openai  # 可选值：openai, gemini, deepseek, siliconflow, zhipu, custom
MCP_LOG_LEVEL=info                 # 日志级别

Docker 环境下使用 MCP

在 Docker 环境中，MCP Server 会与 Web 应用一起运行，您可以通过 Web 应用的相同端口访问 MCP 服务，路径为 /mcp。

例如，如果您将容器的 80 端口映射到主机的 8081 端口：

docker run -d -p 8081:80 \
  -e VITE_OPENAI_API_KEY=your-openai-key \
  -e MCP_DEFAULT_MODEL_PROVIDER=openai \
  --name prompt-optimizer \
  linshen/prompt-optimizer

那么 MCP Server 将可以通过 http://localhost:8081/mcp 访问。

Claude Desktop 集成示例

要在 Claude Desktop 中使用 Prompt Optimizer，您需要在 Claude Desktop 的配置文件中添加服务配置。

找到 Claude Desktop 的配置目录：
- Windows: %APPDATA%\Claude\services
- macOS: ~/Library/Application Support/Claude/services
- Linux: ~/.config/Claude/services
编辑或创建 services.json 文件，添加以下内容：

{
  "services": [
    {
      "name": "Prompt Optimizer",
      "url": "http://localhost:8081/mcp"
    }
  ]
}

请确保将 localhost:8081 替换为您实际部署 Prompt Optimizer 的地址和端口。

可用工具

optimize-user-prompt: 优化用户提示词以提高 LLM 性能
optimize-system-prompt: 优化系统提示词以提高 LLM 性能
iterate-prompt: 对已经成熟/完善的提示词进行定向迭代优化

更多详细信息，请查看 MCP 服务器用户指南。

⚙️ API密钥配置

点击查看API密钥配置方法

方式一：通过界面配置（推荐）

点击界面右上角的"⚙️设置"按钮
选择"模型管理"选项卡
点击需要配置的模型（如OpenAI、Gemini、DeepSeek等）
在弹出的配置框中输入对应的API密钥
点击"保存"即可

支持的模型：OpenAI、Gemini、DeepSeek、Zhipu智谱、SiliconFlow、自定义API（OpenAI兼容接口）

除了API密钥，您还可以在模型配置界面为每个模型单独设置高级LLM参数。这些参数通过一个名为 llmParams 的字段进行配置，它允许您以键值对的形式指定LLM SDK支持的任何参数，从而更精细地控制模型行为。

高级LLM参数配置示例：

OpenAI/兼容API: {"temperature": 0.7, "max_tokens": 4096, "timeout": 60000}
Gemini: {"temperature": 0.8, "maxOutputTokens": 2048, "topP": 0.95}
DeepSeek: {"temperature": 0.5, "top_p": 0.9, "frequency_penalty": 0.1}

有关 llmParams 的更详细说明和配置指南，请参阅 LLM参数配置指南。

方式二：通过环境变量配置

Docker部署时通过 -e 参数配置环境变量：

-e VITE_OPENAI_API_KEY=your_key
-e VITE_GEMINI_API_KEY=your_key
-e VITE_DEEPSEEK_API_KEY=your_key
-e VITE_ZHIPU_API_KEY=your_key
-e VITE_SILICONFLOW_API_KEY=your_key
-e VITE_CUSTOM_API_KEY=your_custom_api_key
-e VITE_CUSTOM_API_BASE_URL=your_custom_api_base_url
-e VITE_CUSTOM_API_MODEL=your_custom_model_name

本地开发

详细文档可查看开发文档

点击查看本地开发命令

# 1. 克隆项目
git clone https://github.com/linshenkx/prompt-optimizer.git
cd prompt-optimizer

# 2. 安装依赖
pnpm install

# 3. 启动开发服务
pnpm dev               # 主开发命令：构建core/ui并运行web应用
pnpm dev:web          # 仅运行web应用
pnpm dev:fresh        # 完整重置并重新启动开发环境

🗺️ 开发路线

基础功能开发
Web应用发布
Chrome插件发布
国际化支持
支持系统提示词优化和用户提示词优化
桌面应用发布
mcp服务发布

详细的项目状态可查看项目状态文档

📖 相关文档

文档索引 - 所有文档的索引
技术开发指南 - 技术栈和开发规范
LLM参数配置指南 - 高级LLM参数配置详细说明
项目结构 - 详细的项目结构说明
项目状态 - 当前进度和计划
产品需求 - 产品需求文档
Vercel部署指南 - Vercel部署详细说明

Star History

常见问题

点击查看常见问题解答

API连接问题

Q1: 为什么配置好API密钥后仍然无法连接到模型服务？

A: 大多数连接失败是由跨域问题（CORS）导致的。由于本项目是纯前端应用，浏览器出于安全考虑会阻止直接访问不同源的API服务。模型服务如未正确配置CORS策略，会拒绝来自浏览器的直接请求。

Q2: 如何解决本地Ollama的连接问题？

A: Ollama完全支持OpenAI标准接口，只需配置正确的跨域策略：

设置环境变量 OLLAMA_ORIGINS=* 允许任意来源的请求
如仍有问题，设置 OLLAMA_HOST=0.0.0.0:11434 监听任意IP地址

Q3: 如何解决商业API（如Nvidia的DS API、字节跳动的火山API）的跨域问题？

A: 这些平台通常有严格的跨域限制，推荐以下解决方案：

使用Vercel代理（便捷方案）
- 使用在线版本：prompt.always200.com
- 或自行部署到Vercel平台
- 在模型设置中勾选"使用Vercel代理"选项
- 请求流向：浏览器→Vercel→模型服务提供商
- 详细步骤请参考 Vercel部署指南
使用自部署的API中转服务（可靠方案）
- 部署如OneAPI等开源API聚合/代理工具
- 在设置中配置为自定义API端点
- 请求流向：浏览器→中转服务→模型服务提供商

Q4: Vercel代理有什么缺点或风险？

A: 使用Vercel代理可能会触发某些模型服务提供商的风控机制。部分厂商可能会将来自Vercel的请求判定为代理行为，从而限制或拒绝服务。如遇此问题，建议使用自部署的中转服务。

Q5: 我已正确配置本地模型（如Ollama）的跨域策略，为什么使用在线版依然无法连接？

A: 这是由浏览器的混合内容（Mixed Content）安全策略导致的。出于安全考虑，浏览器会阻止安全的HTTPS页面（如在线版）向不安全的HTTP地址（如您的本地Ollama服务）发送请求。

解决方案：为了绕过此限制，您需要让应用和API处于同一种协议下（例如，都是HTTP）。推荐以下几种方式：

使用桌面版：桌面应用没有浏览器限制，是连接本地模型最稳定可靠的方式。
docker部署：docker部署也是http
使用Chrome插件：插件在某些情况下也可以绕过部分安全限制。

🤝 参与贡献

点击查看贡献指南

Fork 本仓库
创建特性分支 (git checkout -b feature/AmazingFeature)
提交更改 (git commit -m '添加某个特性')
推送到分支 (git push origin feature/AmazingFeature)
提交 Pull Request

提示：使用cursor工具开发时，建议在提交前:

使用"code_review"规则进行代码审查
按照审查报告格式检查:
- 变更的整体一致性
- 代码质量和实现方式
- 测试覆盖情况
- 文档完善程度
根据审查结果进行优化后再提交

👏 贡献者名单

感谢所有为项目做出贡献的开发者！

📄 开源协议

本项目采用 MIT 协议开源。

如果这个项目对你有帮助，请考虑给它一个 Star ⭐️

👥 联系我们

提交 Issue
发起 Pull Request
加入讨论组

llm_engineering

Thu, 10 Jul 2025 15:32:10 +0800

ed-donner/llm_engineering

LLM Engineering - Master AI and LLMs

Your 8 week journey to proficiency starts today

I’m so happy you’re joining me on this path. We’ll be building immensely satisfying projects in the coming weeks. Some will be easy, some will be challenging, many will ASTOUND you! The projects build on each other so you develop deeper and deeper expertise each week. One thing’s for sure: you’re going to have a lot of fun along the way.

Before you begin

I’m here to help you be most successful with your learning! If you hit any snafus, or if you have any ideas on how I can improve the course, please do reach out in the platform or by emailing me direct (ed@edwarddonner.com). It’s always great to connect with people on LinkedIn to build up the community - you’ll find me here:
https://www.linkedin.com/in/eddonner/
And this is new to me, but I’m also trying out X/Twitter at @edwarddonner - if you’re on X, please show me how it’s done 😂

Resources to accompany the course, including the slides and useful links, are here:
https://edwarddonner.com/2024/11/13/llm-engineering-resources/

Instant Gratification instructions for Week 1, Day 1 - with Llama 3.2 not Llama 3.3!

Important note: see my warning about Llama3.3 below - it’s too large for home computers! Stick with llama3.2! Several students have missed this warning…

We will start the course by installing Ollama so you can see results immediately!

Download and install Ollama from https://ollama.com noting that on a PC you might need to have administrator permissions for the install to work properly
On a PC, start a Command prompt / Powershell (Press Win + R, type cmd, and press Enter). On a Mac, start a Terminal (Applications > Utilities > Terminal).
Run ollama run llama3.2 or for smaller machines try ollama run llama3.2:1b - please note steer clear of Meta’s latest model llama3.3 because at 70B parameters that’s way too large for most home computers!
If this doesn’t work: you may need to run ollama serve in another Powershell (Windows) or Terminal (Mac), and try step 3 again. On a PC, you may need to be running in an Admin instance of Powershell.
And if that doesn’t work on your box, I’ve set up this on the cloud. This is on Google Colab, which will need you to have a Google account to sign in, but is free: https://colab.research.google.com/drive/1-_f5XZPsChvfU1sJ0QqCePtIuc55LSdu?usp=sharing

Any problems, please contact me!

Then, Setup instructions

After we do the Ollama quick project, and after I introduce myself and the course, we get to work with the full environment setup.

Hopefully I’ve done a decent job of making these guides bulletproof - but please contact me right away if you hit roadblocks:

PC people please follow the instructions in SETUP-PC.md
Mac people please follow the instructions in SETUP-mac.md
Linux people please follow the instructions in SETUP-linux.md

The are also PDF versions of the setup instructions in this folder if you’d prefer.

An important point on API costs (which are optional! No need to spend if you don’t wish)

During the course, I’ll suggest you try out the leading models at the forefront of progress, known as the Frontier models. I’ll also suggest you run open-source models using Google Colab. These services have some charges, but I’ll keep cost minimal - like, a few cents at a time. And I’ll provide alternatives if you’d prefer not to use them.

Please do monitor your API usage to ensure you’re comfortable with spend; I’ve included links below. There’s no need to spend anything more than a couple of dollars for the entire course. Some AI providers such as OpenAI require a minimum credit like $5 or local equivalent; we should only spend a fraction of it, and you’ll have plenty of opportunity to put it to good use in your own projects. During Week 7 you have an option to spend a bit more if you’re enjoying the process - I spend about $10 myself and the results make me very happy indeed! But it’s not necessary in the least; the important part is that you focus on learning.

Free alternative to Paid APIs

Early in the course, I show you an alternative if you’d rather not spend anything on APIs:
Any time that we have code like:
openai = OpenAI()
You can use this as a direct replacement:
openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')
And also replace model names like gpt-4o-mini with llama3.2.
For week 1 day 1, you can find this in week1/solutions/day1_with_ollama.ipynb.

Below is a full example:

# You need to do this one time on your computer
!ollama pull llama3.2

from openai import OpenAI
MODEL = "llama3.2"
openai = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")

response = openai.chat.completions.create(
 model=MODEL,
 messages=[{"role": "user", "content": "What is 2 + 2?"}]
)

print(response.choices[0].message.content)

How this Repo is organized

There are folders for each of the “weeks”, representing modules of the class, culminating in a powerful autonomous Agentic AI solution in Week 8 that draws on many of the prior weeks.
Follow the setup instructions above, then open the Week 1 folder and prepare for joy.

The most important part

The mantra of the course is: the best way to learn is by DOING. I don’t type all the code during the course; I execute it for you to see the results. You should work along with me or after each lecture, running each cell, inspecting the objects to get a detailed understanding of what’s happening. Then tweak the code and make it your own. There are juicy challenges for you throughout the course. I’d love it if you wanted to submit a Pull Request for your code (instructions here) and I can make your solutions available to others so we share in your progress; as an added benefit, you’ll be recognized in GitHub for your contribution to the repo. While the projects are enjoyable, they are first and foremost designed to be educational, teaching you business skills that can be put into practice in your work.

Starting in Week 3, we’ll also be using Google Colab for running with GPUs

You should be able to use the free tier or minimal spend to complete all the projects in the class. I personally signed up for Colab Pro+ and I’m loving it - but it’s not required.

Learn about Google Colab and set up a Google account (if you don’t already have one) here

The colab links are in the Week folders and also here:

For week 3 day 1, this Google Colab shows what colab can do
For week 3 day 2, here is a colab for the HuggingFace pipelines API
For week 3 day 3, here’s the colab on Tokenizers
For week 3 day 4, we go to a colab with HuggingFace models
For week 3 day 5, we return to colab to make our Meeting Minutes product
For week 7, we will use these Colab books: Day 1 | Day 2 | Days 3 and 4 | Day 5

Monitoring API charges

You can keep your API spend very low throughout this course; you can monitor spend at the dashboards: here for OpenAI, here for Anthropic and here for Google Gemini.

The charges for the exercsies in this course should always be quite low, but if you’d prefer to keep them minimal, then be sure to always choose the cheapest versions of models:

For OpenAI: Always use model gpt-4o-mini in the code instead of gpt-4o
For Anthropic: Always use model claude-3-haiku-20240307 in the code instead of the other Claude models
During week 7, look out for my instructions for using the cheaper dataset

Please do message me or email me at ed@edwarddonner.com if this doesn’t work or if I can help with anything. I can’t wait to hear how you get on.

Other resources

I've put together this webpage with useful resources for the course. This includes links to all the slides.
https://edwarddonner.com/2024/11/13/llm-engineering-resources/
Please keep this bookmarked, and I'll continue to add more useful links there over time.

12-factor-agents

Wed, 09 Jul 2025 15:30:40 +0800

humanlayer/12-factor-agents

12-Factor Agents - Principles for building reliable LLM applications

In the spirit of 12 Factor Apps. The source for this project is public at https://github.com/humanlayer/12-factor-agents, and I welcome your feedback and contributions. Let’s figure this out together!

[!TIP] Missed the AI Engineer World’s Fair? Catch the talk here

Looking for Context Engineering? Jump straight to factor 3

Hi, I’m Dex. I’ve been hacking on AI agents for a while.

I’ve tried every agent framework out there, from the plug-and-play crew/langchains to the “minimalist” smolagents of the world to the “production grade” langraph, griptape, etc.

I’ve talked to a lot of really strong founders, in and out of YC, who are all building really impressive things with AI. Most of them are rolling the stack themselves. I don’t see a lot of frameworks in production customer-facing agents.

I’ve been surprised to find that most of the products out there billing themselves as “AI Agents” are not all that agentic. A lot of them are mostly deterministic code, with LLM steps sprinkled in at just the right points to make the experience truly magical.

Agents, at least the good ones, don’t follow the “here’s your prompt, here’s a bag of tools, loop until you hit the goal” pattern. Rather, they are comprised of mostly just software.

So, I set out to answer:

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

Welcome to 12-factor agents. As every Chicago mayor since Daley has consistently plastered all over the city’s major airports, we’re glad you’re here.

Special thanks to @iantbutler01, @tnm, @hellovai, @stantonk, @balanceiskey, @AdjectiveAllison, @pfbyjy, @a-churchill, and the SF MLOps community for early feedback on this guide.

The Short Version: The 12 Factors

Even if LLMs continue to get exponentially more powerful, there will be core engineering techniques that make LLM-powered software more reliable, more scalable, and easier to maintain.

Visual Nav

How we got here

For a deeper dive on my agent journey and what led us here, check out A Brief History of Software - a quick summary here:

The promise of agents

We’re gonna talk a lot about Directed Graphs (DGs) and their Acyclic friends, DAGs. I’ll start by pointing out that…well…software is a directed graph. There’s a reason we used to represent programs as flow charts.

From code to DAGs

Around 20 years ago, we started to see DAG orchestrators become popular. We’re talking classics like Airflow, Prefect, some predecessors, and some newer ones like (dagster, inggest, windmill). These followed the same graph pattern, with the added benefit of observability, modularity, retries, administration, etc.

The promise of agents

I’m not the first person to say this, but my biggest takeaway when I started learning about agents, was that you get to throw the DAG away. Instead of software engineers coding each step and edge case, you can give the agent a goal and a set of transitions:

And let the LLM make decisions in real time to figure out the path

The promise here is that you write less software, you just give the LLM the “edges” of the graph and let it figure out the nodes. You can recover from errors, you can write less code, and you may find that LLMs find novel solutions to problems.

Agents as loops

As we’ll see later, it turns out this doesn’t quite work.

Let’s dive one step deeper - with agents you’ve got this loop consisting of 3 steps:

LLM determines the next step in the workflow, outputting structured json (“tool calling”)
Deterministic code executes the tool call
The result is appended to the context window
Repeat until the next step is determined to be “done”

initial_event = {"message": "..."}
context = [initial_event]
while True:
  next_step = await llm.determine_next_step(context)
  context.append(next_step)

  if (next_step.intent === "done"):
    return next_step.final_answer

  result = await execute_step(next_step)
  context.append(result)

Our initial context is just the starting event (maybe a user message, maybe a cron fired, maybe a webhook, etc), and we ask the llm to choose the next step (tool) or to determine that we’re done.

Here’s a multi-step example:

GIF Version

]

Why 12-factor agents?

At the end of the day, this approach just doesn’t work as well as we want it to.

In building HumanLayer, I’ve talked to at least 100 SaaS builders (mostly technical founders) looking to make their existing product more agentic. The journey usually goes something like:

Decide you want to build an agent
Product design, UX mapping, what problems to solve
Want to move fast, so grab $FRAMEWORK and get to building
Get to 70-80% quality bar
Realize that 80% isn’t good enough for most customer-facing features
Realize that getting past 80% requires reverse-engineering the framework, prompts, flow, etc.
Start over from scratch

Random Disclaimers

DISCLAIMER: I’m not sure the exact right place to say this, but here seems as good as any: this in BY NO MEANS meant to be a dig on either the many frameworks out there, or the pretty dang smart people who work on them. They enable incredible things and have accelerated the AI ecosystem.

I hope that one outcome of this post is that agent framework builders can learn from the journeys of myself and others, and make frameworks even better.

Especially for builders who want to move fast but need deep control.

DISCLAIMER 2: I’m not going to talk about MCP. I’m sure you can see where it fits in.

DISCLAIMER 3: I’m using mostly typescript, for reasons but all this stuff works in python or any other language you prefer.

Anyways back to the thing…

Design Patterns for great LLM applications

After digging through hundreds of AI libriaries and working with dozens of founders, my instinct is this:

There are some core things that make agents great
Going all in on a framework and building what is essentially a greenfield rewrite may be counter-productive
There are some core principles that make agents great, and you will get most/all of them if you pull in a framework
BUT, the fastest way I’ve seen for builders to get high-quality AI software in the hands of customers is to take small, modular concepts from agent building, and incorporate them into their existing product
These modular concepts from agents can be defined and applied by most skilled software engineers, even if they don’t have an AI background

The fastest way I’ve seen for builders to get good AI software in the hands of customers is to take small, modular concepts from agent building, and incorporate them into their existing product

The 12 Factors (again)

Honorable Mentions / other advice

Factor 13: Pre-fetch all the context you might need

Contribute to this guide here
I talked about a lot of this on an episode of the Tool Use podcast in March 2025
I write about some of this stuff at The Outer Loop
I do webinars about Maximizing LLM Performance with @hellovai
We build OSS agents with this methodology under got-agents/agents
We ignored all our own advice and built a framework for running distributed agents in kubernetes
Other links from this guide:

Contributors

Thanks to everyone who has contributed to 12-factor agents!

Versions

This is the current version of 12-factor agents, version 1.0. There is a draft of version 1.1 on the v1.1 branch. There are a few Issues to track work on v1.1.

License

All content and images are licensed under a CC BY-SA 4.0 License

Code is licensed under the Apache 2.0 License

ragflow

Thu, 19 Jun 2025 15:29:58 +0800

infiniflow/ragflow

Document | Roadmap | Twitter | Discord | Demo

📕 Table of Contents

💡 What is RAGFlow?
🎮 Demo
📌 Latest Updates
🌟 Key Features
🔎 System Architecture
🎬 Get Started
🔧 Configurations
🔧 Build a docker image without embedding models
🔧 Build a docker image including embedding models
🔨 Launch service from source for development
📚 Documentation
📜 Roadmap
🏄 Community
🙌 Contributing

💡 What is RAGFlow?

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.

🎮 Demo

Try our demo at https://demo.ragflow.io.

🔥 Latest Updates

2025-05-23 Adds a Python/JavaScript code executor component to Agent.
2025-05-05 Supports cross-language query.
2025-03-19 Supports using a multi-modal model to make sense of images within PDF or DOCX files.
2025-02-28 Combined with Internet search (Tavily), supports reasoning like Deep Research for any LLMs.
2024-12-18 Upgrades Document Layout Analysis model in DeepDoc.
2024-08-22 Support text to SQL statements through RAG.

🎉 Stay Tuned

⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new releases! 🌟

🌟 Key Features

🍭 “Quality in, quality out”

Deep document understanding-based knowledge extraction from unstructured data with complicated formats.
Finds “needle in a data haystack” of literally unlimited tokens.

🍱 Template-based chunking

Intelligent and explainable.
Plenty of template options to choose from.

🌱 Grounded citations with reduced hallucinations

Visualization of text chunking to allow human intervention.
Quick view of the key references and traceable citations to support grounded answers.

🍔 Compatibility with heterogeneous data sources

Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.

🛀 Automated and effortless RAG workflow

Streamlined RAG orchestration catered to both personal and large businesses.
Configurable LLMs as well as embedding models.
Multiple recall paired with fused re-ranking.
Intuitive APIs for seamless integration with business.

🔎 System Architecture

🎬 Get Started

📝 Prerequisites

CPU >= 4 cores
RAM >= 16 GB
Disk >= 50 GB
Docker >= 24.0.0 & Docker Compose >= v2.26.1
gVisor: Required only if you intend to use the code executor (sandbox) feature of RAGFlow.

[!TIP] If you have not installed Docker on your local machine (Windows, Mac, or Linux), see Install Docker Engine.

🚀 Start up the server

Ensure vm.max_map_count >= 262144:
To check the value of vm.max_map_count:
1

$ sysctl vm.max_map_count
Reset vm.max_map_count to a value at least 262144 if it is not.
1 2

# In this case, we set it to 262144: $ sudo sysctl -w vm.max_map_count=262144
This change will be reset after a system reboot. To ensure your change remains permanent, add or update the vm.max_map_count value in /etc/sysctl.conf accordingly:
1

vm.max_map_count=262144

Clone the repo:

`1`	`$ git clone https://github.com/infiniflow/ragflow.git`

Start up the server using the pre-built Docker images:

[!CAUTION] All Docker images are built for x86 platforms. We don’t currently offer Docker images for ARM64. If you are on an ARM64 platform, follow this guide to build a Docker image compatible with your system.

The command below downloads the v0.19.1-slim edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from v0.19.1-slim, update the RAGFLOW_IMAGE variable accordingly in docker/.env before using docker compose to start the server. For example: set RAGFLOW_IMAGE=infiniflow/ragflow:v0.19.1 for the full edition v0.19.1.

$ cd ragflow/docker
# Use CPU for embedding and DeepDoc tasks:
$ docker compose -f docker-compose.yml up -d

# To use GPU to accelerate embedding and DeepDoc tasks:
# docker compose -f docker-compose-gpu.yml up -d

RAGFlow image tag	Image size (GB)	Has embedding models?	Stable?
v0.19.1	≈9	:heavy_check_mark:	Stable release
v0.19.1-slim	≈2	❌	Stable release
nightly	≈9	:heavy_check_mark:	Unstable nightly build
nightly-slim	≈2	❌	Unstable nightly build

Check the server status after having the server up and running:

`1`	`$ docker logs -f ragflow-server`

The following output confirms a successful launch of the system:


      ____   ___    ______ ______ __
     / __ \ /   |  / ____// ____// /____  _      __
    / /_/ // /| | / / __ / /_   / // __ \| | /| / /
   / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
  /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/

 * Running on all addresses (0.0.0.0)

If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a network anormal error because, at that moment, your RAGFlow may not be fully initialized.

In your web browser, enter the IP address of your server and log in to RAGFlow.

With the default settings, you only need to enter http://IP_OF_YOUR_MACHINE (sans port number) as the default HTTP serving port 80 can be omitted when using the default configurations.
In service_conf.yaml.template, select the desired LLM factory in user_default_llm and update the API_KEY field with the corresponding API key.

See llm_api_key_setup for more information.

The show is on!

🔧 Configurations

When it comes to system configurations, you will need to manage the following files:

.env: Keeps the fundamental setups for the system, such as SVR_HTTP_PORT, MYSQL_PASSWORD, and MINIO_PASSWORD.
service_conf.yaml.template: Configures the back-end services. The environment variables in this file will be automatically populated when the Docker container starts. Any environment variables set within the Docker container will be available for use, allowing you to customize service behavior based on the deployment environment.
docker-compose.yml: The system relies on docker-compose.yml to start up.

The ./docker/README file provides a detailed description of the environment settings and service configurations which can be used as ${ENV_VARS} in the service_conf.yaml.template file.

To update the default HTTP serving port (80), go to docker-compose.yml and change 80:80 to <YOUR_SERVING_PORT>:80.

Updates to the above configurations require a reboot of all containers to take effect:

`1`	`$ docker compose -f docker-compose.yml up -d`

Switch doc engine from Elasticsearch to Infinity

RAGFlow uses Elasticsearch by default for storing full text and vectors. To switch to Infinity, follow these steps:

Stop all running containers:

`1`	`$ docker compose -f docker/docker-compose.yml down -v`

[!WARNING] -v will delete the docker container volumes, and the existing data will be cleared.

Set DOC_ENGINE in docker/.env to infinity.

Start the containers:

`1`	`$ docker compose -f docker-compose.yml up -d`

[!WARNING] Switching to Infinity on a Linux/arm64 machine is not yet officially supported.

🔧 Build a Docker image without embedding models

This image is approximately 2 GB in size and relies on external LLM and embedding services.

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git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
docker build --platform linux/amd64 --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .

🔧 Build a Docker image including embedding models

This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.

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git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .

🔨 Launch service from source for development

Install uv, or skip this step if it is already installed:
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pipx install uv pre-commit

Clone the source code and install Python dependencies:

git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
uv sync --python 3.10 --all-extras # install RAGFlow dependent python modules
uv run download_deps.py
pre-commit install

Launch the dependent services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:
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docker compose -f docker/docker-compose-base.yml up -d
Add the following line to /etc/hosts to resolve all hosts specified in docker/.env to 127.0.0.1:
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127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
If you cannot access HuggingFace, set the HF_ENDPOINT environment variable to use a mirror site:
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export HF_ENDPOINT=https://hf-mirror.com

If your operating system does not have jemalloc, please install it as follows:

# ubuntu
sudo apt-get install libjemalloc-dev
# centos
sudo yum install jemalloc

Launch backend service:

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source .venv/bin/activate
export PYTHONPATH=$(pwd)
bash docker/launch_backend_service.sh

Install frontend dependencies:
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cd web npm install
Launch frontend service:
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npm run dev
The following output confirms a successful launch of the system:
Stop RAGFlow front-end and back-end service after development is complete:
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pkill -f "ragflow_server.py|task_executor.py"

📚 Documentation

📜 Roadmap

See the RAGFlow Roadmap 2025

🏄 Community

🙌 Contributing

RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our Contribution Guidelines first.

servers

Wed, 11 Jun 2025 15:30:18 +0800

modelcontextprotocol/servers

Model Context Protocol servers

This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community built servers and additional resources.

The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources. Each MCP server is implemented with either the Typescript MCP SDK or Python MCP SDK.

Note: Lists in this README are maintained in alphabetical order to minimize merge conflicts when adding new items.

🌟 Reference Servers

These servers aim to demonstrate MCP features and the TypeScript and Python SDKs.

Everything - Reference / test server with prompts, resources, and tools
Fetch - Web content fetching and conversion for efficient LLM usage
Filesystem - Secure file operations with configurable access controls
Git - Tools to read, search, and manipulate Git repositories
Memory - Knowledge graph-based persistent memory system
Sequential Thinking - Dynamic and reflective problem-solving through thought sequences
Time - Time and timezone conversion capabilities

Archived

The following reference servers are now archived and can be found at servers-archived.

AWS KB Retrieval - Retrieval from AWS Knowledge Base using Bedrock Agent Runtime
Brave Search - Web and local search using Brave’s Search API
EverArt - AI image generation using various models
GitHub - Repository management, file operations, and GitHub API integration
GitLab - GitLab API, enabling project management
Google Drive - File access and search capabilities for Google Drive
Google Maps - Location services, directions, and place details
PostgreSQL - Read-only database access with schema inspection
Puppeteer - Browser automation and web scraping
Redis - Interact with Redis key-value stores
Sentry - Retrieving and analyzing issues from Sentry.io
Slack - Channel management and messaging capabilities
Sqlite - Database interaction and business intelligence capabilities

🤝 Third-Party Servers

🎖️ Official Integrations

Official integrations are maintained by companies building production ready MCP servers for their platforms.

21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers.
Adfin - The only platform you need to get paid - all payments in one place, invoicing and accounting reconciliations with Adfin.
AgentQL - Enable AI agents to get structured data from unstructured web with AgentQL.
AgentRPC - Connect to any function, any language, across network boundaries using AgentRPC.
Aiven - Navigate your Aiven projects and interact with the PostgreSQL®, Apache Kafka®, ClickHouse® and OpenSearch® services
Alation - Unlock the power of the enterprise Data Catalog by harnessing tools provided by the Alation MCP server.
Algolia MCP Algolia MCP Server exposes a natural language interface to query, inspect, and manage Algolia indices and configs. Useful for monitoring, debugging and optimizing search performance within your agentic workflows. See demo.
Alibaba Cloud RDS - An MCP server designed to interact with the Alibaba Cloud RDS OpenAPI, enabling programmatic management of RDS resources via an LLM.
Alibaba Cloud AnalyticDB for MySQL - Connect to a AnalyticDB for MySQL cluster for getting database or table metadata, querying and analyzing data.It will be supported to add the openapi for cluster operation in the future.
Alibaba Cloud OPS - Manage the lifecycle of your Alibaba Cloud resources with CloudOps Orchestration Service and Alibaba Cloud OpenAPI.
Alibaba Cloud OpenSearch - This MCP server equips AI Agents with tools to interact with OpenSearch through a standardized and extensible interface.
Apache IoTDB - MCP Server for Apache IoTDB database and its tools
Apify - Actors MCP Server: Use 3,000+ pre-built cloud tools to extract data from websites, e-commerce, social media, search engines, maps, and more
APIMatic MCP - APIMatic MCP Server is used to validate OpenAPI specifications using APIMatic. The server processes OpenAPI files and returns validation summaries by leveraging APIMatic’s API.
Apollo MCP Server - Connect your GraphQL APIs to AI agents
Arize Phoenix - Inspect traces, manage prompts, curate datasets, and run experiments using Arize Phoenix, an open-source AI and LLM observability tool.
Asgardeo - MCP server to interact with your Asgardeo organization through LLM tools.
Astra DB - Comprehensive tools for managing collections and documents in a DataStax Astra DB NoSQL database with a full range of operations such as create, update, delete, find, and associated bulk actions.
Atlan - The Atlan Model Context Protocol server allows you to interact with the Atlan services through multiple tools.
Audiense Insights - Marketing insights and audience analysis from Audiense reports, covering demographic, cultural, influencer, and content engagement analysis.
AWS - Specialized MCP servers that bring AWS best practices directly to your development workflow.
Axiom - Query and analyze your Axiom logs, traces, and all other event data in natural language
Azure - The Azure MCP Server gives MCP Clients access to key Azure services and tools like Azure Storage, Cosmos DB, the Azure CLI, and more.
Bankless Onchain - Query Onchain data, like ERC20 tokens, transaction history, smart contract state.
BICScan - Risk score / asset holdings of EVM blockchain address (EOA, CA, ENS) and even domain names.
Bitrise - Chat with your builds, CI, and more.
Box - Interact with the Intelligent Content Management platform through Box AI.
Browserbase - Automate browser interactions in the cloud (e.g. web navigation, data extraction, form filling, and more)
BrowserStack - Access BrowserStack’s Test Platform to debug, write and fix tests, do accessibility testing and more.
Burp Suite - MCP Server extension allowing AI clients to connect to Burp Suite
Cartesia - Connect to the Cartesia voice platform to perform text-to-speech, voice cloning etc.
Chargebee - MCP Server that connects AI agents to Chargebee platform.
Chiki StudIO - Create your own configurable MCP servers purely via configuration (no code), with instructions, prompts, and tools support.
Chroma - Embeddings, vector search, document storage, and full-text search with the open-source AI application database
Chronulus AI - Predict anything with Chronulus AI forecasting and prediction agents.
CircleCI - Enable AI Agents to fix build failures from CircleCI.
ClickHouse - Query your ClickHouse database server.
Cloudflare - Deploy, configure & interrogate your resources on the Cloudflare developer platform (e.g. Workers/KV/R2/D1)
Codacy - Interact with Codacy API to query code quality issues, vulnerabilities, and coverage insights about your code.
CodeLogic - Interact with CodeLogic, a Software Intelligence platform that graphs complex code and data architecture dependencies, to boost AI accuracy and insight.
Comet Opik - Query and analyze your Opik logs, traces, prompts and all other telemtry data from your LLMs in natural language.
Confluent - Interact with Confluent Kafka and Confluent Cloud REST APIs.
Convex - Introspect and query your apps deployed to Convex.
Couchbase - Interact with the data stored in Couchbase clusters.
CRIC Wuye AI - Interact with capabilities of the CRIC Wuye AI platform, an intelligent assistant specifically for the property management industry.
Dart - Interact with task, doc, and project data in Dart, an AI-native project management tool
DataHub - Search your data assets, traverse data lineage, write SQL queries, and more using DataHub metadata.
DexPaprika (CoinPaprika) - Access real-time DEX data, liquidity pools, token information, and trading analytics across multiple blockchain networks with DexPaprika by CoinPaprika.
DevHub - Manage and utilize website content within the DevHub CMS platform
DevRev - An MCP server to integrate with DevRev APIs to search through your DevRev Knowledge Graph where objects can be imported from diff. Sources listed here.
Dynatrace - Manage and interact with the Dynatrace Platform for real-time observability and monitoring.
E2B - Run code in secure sandboxes hosted by E2B
Edgee - Deploy and manage Edgee components and projects
EduBase - Interact with EduBase, a comprehensive e-learning platform with advanced quizzing, exam management, and content organization capabilities
Elasticsearch - Query your data in Elasticsearch
eSignatures - Contract and template management for drafting, reviewing, and sending binding contracts.
Exa - Search Engine made for AIs by Exa
Fewsats - Enable AI Agents to purchase anything in a secure way using Fewsats
Fibery - Perform queries and entity operations in your Fibery workspace.
Financial Datasets - Stock market API made for AI agents
Firecrawl - Extract web data with Firecrawl
Fireproof - Immutable ledger database with live synchronization
Github - GitHub’s official MCP Server
GibsonAI - AI-Powered Cloud databases: Build, migrate, and deploy database instances with AI
Gitea - Interact with Gitea instances with MCP.
Gitee - Gitee API integration, repository, issue, and pull request management, and more.
Glean - Enterprise search and chat using Glean’s API.
Gyazo - Search, fetch, upload, and interact with Gyazo images, including metadata and OCR data.
gotoHuman - Human-in-the-loop platform - Allow AI agents and automations to send requests for approval to your gotoHuman inbox.
Grafana - Search dashboards, investigate incidents and query datasources in your Grafana instance
Grafbase - Turn your GraphQL API into an efficient MCP server with schema intelligence in a single command.
Graphlit - Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a searchable Graphlit project.
GreptimeDB - Provides AI assistants with a secure and structured way to explore and analyze data in GreptimeDB.
Heroku - Interact with the Heroku Platform through LLM-driven tools for managing apps, add-ons, dynos, databases, and more.
Hologres - Connect to a Hologres instance, get table metadata, query and analyze data.
Honeycomb Allows Honeycomb Enterprise customers to query and analyze their data, alerts, dashboards, and more; and cross-reference production behavior with the codebase.
HubSpot - Connect, manage, and interact with HubSpot CRM data
Hyperbrowser - Hyperbrowser is the next-generation platform empowering AI agents and enabling effortless, scalable browser automation.
IBM wxflows - Tool platform by IBM to build, test and deploy tools for any data source
ForeverVM - Run Python in a code sandbox.
Inbox Zero - AI personal assistant for email Inbox Zero
Inkeep - RAG Search over your content powered by Inkeep
Integration App - Interact with any other SaaS applications on behalf of your customers.
JetBrains – Work on your code with JetBrains IDEs
Kagi Search - Search the web using Kagi’s search API
Keboola - Build robust data workflows, integrations, and analytics on a single intuitive platform.
Klavis ReportGen - Create professional reports from a simple user query.
KWDB - Reading, writing, querying, modifying data, and performing DDL operations with data in your KWDB Database.
Lara Translate - MCP Server for Lara Translate API, enabling powerful translation capabilities with support for language detection and context-aware translations.
Logfire - Provides access to OpenTelemetry traces and metrics through Logfire.
Langfuse Prompt Management - Open-source tool for collaborative editing, versioning, evaluating, and releasing prompts.
LaunchDarkly - LaunchDarkly is a continuous delivery platform that provides feature flags as a service and allows developers to iterate quickly and safely.
Linear - Search, create, and update Linear issues, projects, and comments.
Lingo.dev - Make your AI agent speak every language on the planet, using Lingo.dev Localization Engine.
Litmus.io - Official MCP server for configuring Litmus Edge for Industrial Data Collection, Edge Analytics & Industrial AI.
Mailgun - Interact with Mailgun API.
Make - Turn your Make scenarios into callable tools for AI assistants.
MCP Toolbox for Databases - Open source MCP server specializing in easy, fast, and secure tools for Databases. Supports AlloyDB, BigQuery, Bigtable, Cloud SQL, Dgraph, MySQL, Neo4j, Postgres, Spanner, and more.
Meilisearch - Interact & query with Meilisearch (Full-text & semantic search API)
Memgraph - Query your data in Memgraph graph database.
Metoro - Query and interact with kubernetes environments monitored by Metoro
Mercado Pago - Mercado Pago’s official MCP server.
Microsoft Clarity - Official MCP Server to get your behavioral analytics data and insights from Clarity
Microsoft Dataverse - Chat over your business data using NL - Discover tables, run queries, retrieve data, insert or update records, and execute custom prompts grounded in business knowledge and context.
Milvus - Search, Query and interact with data in your Milvus Vector Database.
Momento - Momento Cache lets you quickly improve your performance, reduce costs, and handle load at any scale.
MongoDB - Both MongoDB Community Server and MongoDB Atlas are supported.
MotherDuck - Query and analyze data with MotherDuck and local DuckDB
Needle - Production-ready RAG out of the box to search and retrieve data from your own documents.
Neo4j - Neo4j graph database server (schema + read/write-cypher) and separate graph database backed memory
Neon - Interact with the Neon serverless Postgres platform
Netlify - Create, build, deploy, and manage your websites with Netlify web platform.
Notion - This project implements an MCP server for the Notion API.
OceanBase - MCP Server for OceanBase database and its tools
Octagon - Deliver real-time investment research with extensive private and public market data.
OlaMaps - Official Ola Maps MCP Server for services like geocode, directions, place details and many more.
OP.GG - Access real-time gaming data across popular titles like League of Legends, TFT, and Valorant, offering champion analytics, esports schedules, meta compositions, and character statistics.
OpsLevel - Official MCP Server for OpsLevel.
Oxylabs - Scrape websites with Oxylabs Web API, supporting dynamic rendering and parsing for structured data extraction.
Paddle - Interact with the Paddle API. Manage product catalog, billing and subscriptions, and reports.
Pagos - Interact with the Pagos API. Query Credit Card BIN Data with more to come.
PayPal - PayPal’s official MCP server.
Perplexity - An MCP server that connects to Perplexity’s Sonar API, enabling real-time web-wide research in conversational AI.
Pinecone - Pinecone’s developer MCP Server assist developers in searching documentation and managing data within their development environment.
Pinecone Assistant - Retrieves context from your Pinecone Assistant knowledge base.
Prisma - Create and manage Prisma Postgres databases
Pulumi - Deploy and manage cloud infrastructure using Pulumi.
Pure.md - Reliably access web content in markdown format with pure.md (bot detection avoidance, proxy rotation, and headless JS rendering built in).
Put.io - Interact with your Put.io account to download torrents.
Ragie - Retrieve context from your Ragie (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more.
Redis - The Redis official MCP Server offers an interface to manage and search data in Redis.
Redis Cloud API - The Redis Cloud API MCP Server allows you to manage your Redis Cloud resources using natural language.
Snyk - Enhance security posture by embedding Snyk vulnerability scanning directly into agentic workflows.
Qdrant - Implement semantic memory layer on top of the Qdrant vector search engine
Ramp - Interact with Ramp’s Developer API to run analysis on your spend and gain insights leveraging LLMs
Raygun - Interact with your crash reporting and real using monitoring data on your Raygun account
Rember - Create spaced repetition flashcards in Rember to remember anything you learn in your chats
Riza - Arbitrary code execution and tool-use platform for LLMs by Riza
Root Signals - Improve and quality control your outputs with evaluations using LLM-as-Judge
Search1API - One API for Search, Crawling, and Sitemaps
ScreenshotOne - Render website screenshots with ScreenshotOne
Semgrep - Enable AI agents to secure code with Semgrep.
SingleStore - Interact with the SingleStore database platform
StarRocks - Interact with StarRocks
Stripe - Interact with Stripe API
Tavily - Search engine for AI agents (search + extract) powered by Tavily
Terraform - Seamlessly integrate with Terraform ecosystem, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development powered by Terraform
Thirdweb - Read/write to over 2k blockchains, enabling data querying, contract analysis/deployment, and transaction execution, powered by Thirdweb
Tianji - Interact with Tianji platform whatever selfhosted or cloud platform, powered by Tianji.
TiDB - MCP Server to interact with TiDB database platform.
Tinybird - Interact with Tinybird serverless ClickHouse platform
Tldv - Connect your AI agents to Google-Meet, Zoom & Microsoft Teams through tl;dv
UnifAI - Dynamically search and call tools using UnifAI Network
Unstructured - Set up and interact with your unstructured data processing workflows in Unstructured Platform
Upstash - Manage Redis databases and run Redis commands on Upstash with natural language.
Vectorize - Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.
Verbwire - Deploy smart contracts, mint NFTs, manage IPFS storage, and more through the Verbwire API
Verodat - Interact with Verodat AI Ready Data platform
VeyraX - Single tool to control all 100+ API integrations, and UI components
WayStation - Universal MCP server to connect to popular productivity tools such as Notion, Monday, AirTable, and many more
WaveSpeed - WaveSpeed MCP server providing AI agents with image and video generation capabilities.
Xero - Interact with the accounting data in your business using our official MCP server
YugabyteDB - MCP Server to interact with your YugabyteDB database
Zapier - Connect your AI Agents to 8,000 apps instantly.
ZenML - Interact with your MLOps and LLMOps pipelines through your ZenML MCP server

🌎 Community Servers

A growing set of community-developed and maintained servers demonstrates various applications of MCP across different domains.

Note: Community servers are untested and should be used at your own risk. They are not affiliated with or endorsed by Anthropic.

1Panel - MCP server implementation that provides 1Panel interaction.
A2A - An MCP server that bridges the Model Context Protocol (MCP) with the Agent-to-Agent (A2A) protocol, enabling MCP-compatible AI assistants (like Claude) to seamlessly interact with A2A agents.
Ableton Live - an MCP server to control Ableton Live.
Ableton Live (by ahujasid) - Ableton integration allowing prompt enabled music creation.
Actor Critic Thinking - Actor-critic thinking for performance evaluation
Agentset - RAG for your knowledge base connected to Agentset.
AI Agent Marketplace Index - MCP server to search more than 5000+ AI agents and tools of various categories from AI Agent Marketplace Index and monitor traffic of AI Agents.
Airbnb - Provides tools to search Airbnb and get listing details.
Airflow - A MCP Server that connects to Apache Airflow using official python client.
Airtable - Read and write access to Airtable databases, with schema inspection.
Airtable - Airtable Model Context Protocol Server.
Algorand - A comprehensive MCP server for tooling interactions (40+) and resource accessibility (60+) plus many useful prompts for interacting with the Algorand blockchain.
AlphaVantage - MCP server for stock market data API AlphaVantage
Amadeus (by donghyun-chae) - An MCP server to access, explore, and interact with Amadeus Flight Offers Search API for retrieving detailed flight options, including airline, times, duration, and pricing data.
Amazon Ads - MCP Server that provides interaction capabilities with Amazon Advertising through MarketplaceAdPros/
Anki - An MCP server for interacting with your Anki decks and cards.
AntV Chart - A Model Context Protocol server for generating 15+ visual charts using AntV.
Any Chat Completions - Interact with any OpenAI SDK Compatible Chat Completions API like OpenAI, Perplexity, Groq, xAI and many more.
Apache Gravitino(incubating) - Allow LLMs to explore metadata of structured data and unstructured data with Gravitino, and perform data governance tasks including tagging/classification.
APIWeaver - An MCP server that dynamically creates MCP servers from web API configurations. This allows you to easily integrate any REST API, GraphQL endpoint, or web service into an MCP-compatible tool that can be used by AI assistants like Claude.
Apple Books - Interact with your library on Apple Books, manage your book collection, summarize highlights, notes, and much more.
Apple Calendar - An MCP server that allows you to interact with your MacOS Calendar through natural language, including features such as event creation, modification, schedule listing, finding free time slots etc.
Apple Script - MCP server that lets LLM run AppleScript code to to fully control anything on Mac, no setup needed.
Aranet4 - MCP Server to manage your Aranet4 CO2 sensor. Fetch data and store in a local SQLite. Ask questions about historical data.
ArangoDB - MCP Server that provides database interaction capabilities through ArangoDB.
Arduino - MCP Server that enables AI-powered robotics using Claude AI and Arduino (ESP32) for real-world automation and interaction with robots.
arXiv API - An MCP server that enables interacting with the arXiv API using natural language.
arxiv-latex-mcp - MCP server that fetches and processes arXiv LaTeX sources for precise interpretation of mathematical expressions in papers.
Atlassian - Interact with Atlassian Cloud products (Confluence and Jira) including searching/reading Confluence spaces/pages, accessing Jira issues, and project metadata.
Atlassian Server (by phuc-nt) - An MCP server that connects AI agents (Cline, Claude Desktop, Cursor, etc.) to Atlassian Jira & Confluence, enabling data queries and actions through the Model Context Protocol.
Attestable MCP - An MCP server running inside a trusted execution environment (TEE) via Gramine, showcasing remote attestation using RA-TLS. This allows an MCP client to verify the server before conencting.
Audius - Audius + AI = Atris. Interact with fans, stream music, tip your favorite artists, and more on Audius: all through Claude.
AWS - Perform operations on your AWS resources using an LLM.
AWS Athena - A MCP server for AWS Athena to run SQL queries on Glue Catalog.
AWS Cognito - A MCP server that connects to AWS Cognito for authentication and user management.
AWS Cost Explorer - Optimize your AWS spend (including Amazon Bedrock spend) with this MCP server by examining spend across regions, services, instance types and foundation models (demo video).
AWS Resources Operations - Run generated python code to securely query or modify any AWS resources supported by boto3.
AWS S3 - A sample MCP server for AWS S3 that flexibly fetches objects from S3 such as PDF documents.
Azure ADX - Query and analyze Azure Data Explorer databases.
Azure DevOps - An MCP server that provides a bridge to Azure DevOps services, enabling AI assistants to query and manage work items.
Azure MCP Hub - A curated list of all MCP servers and related resources for Azure developers by Arun Sekhar
Azure OpenAI DALL-E 3 MCP Server - A MCP server for Azure OpenAI DALL-E 3 service to generate image from text.
Azure Wiki Search - An MCP that enables AI to query the wiki hosted on Azure Devops Wiki.
Baidu AI Search - Web search with Baidu Cloud’s AI Search
BambooHR MCP - An MCP server that interfaces with the BambooHR APIs, providing access to employee data, time tracking, and HR management features.
Base Free USDC Transfer - Send USDC on Base for free using Claude AI! Built with Coinbase CDP.
Basic Memory - Local-first knowledge management system that builds a semantic graph from Markdown files, enabling persistent memory across conversations with LLMs.
BigQuery (by LucasHild) - This server enables LLMs to inspect database schemas and execute queries on BigQuery.
BigQuery (by ergut) - Server implementation for Google BigQuery integration that enables direct BigQuery database access and querying capabilities
Bilibili - This MCP server provides tools to fetch Bilibili user profiles, video metadata, search videos, and more.
Bing Web Search API (by hanchunglee) - Server implementation for Microsoft Bing Web Search API.
Bitable MCP (by lloydzhou) - MCP server provides access to Lark Bitable through the Model Context Protocol. It allows users to interact with Bitable tables using predefined tools.
Blender (by ahujasid) - Blender integration allowing prompt enabled 3D scene creation, modeling and manipulation.
BreakoutRoom - Agents accomplishing goals together in p2p rooms
browser-use (by co-browser) - browser-use MCP server with dockerized playwright + chromium + vnc. supports stdio & resumable http.
BrowserLoop - An MCP server for taking screenshots of web pages using Playwright. Supports high-quality capture with configurable formats, viewport sizes, cookie-based authentication, and both full page and element-specific screenshots.
Bsc-mcp The first MCP server that serves as the bridge between AI and BNB Chain, enabling AI agents to execute complex on-chain operations through seamless integration with the BNB Chain, including transfer, swap, launch, security check on any token and even more.
BVG MCP Server - (Unofficial) - Unofficial MCP server for Berliner Verkehrsbetriebe Api.
Calculator - This server enables LLMs to use calculator for precise numerical calculations.
Calendly - Calendly MCP server from agentr that provides support for managing events and scheduling via Calendly.
CCTV VMS MCP - A Model Context Protocol (MCP) server designed to connect to a CCTV recording program (VMS) to retrieve recorded and live video streams. It also provides tools to control the VMS software, such as showing live or playback dialogs for specific channels at specified times.
CFBD API - An MCP server for the College Football Data API.
ChatMCP – An Open Source Cross-platform GUI Desktop application compatible with Linux, macOS, and Windows, enabling seamless interaction with MCP servers across dynamically selectable LLMs, by AIQL
ChatSum - Query and Summarize chat messages with LLM. by mcpso
Chess.com - Access Chess.com player data, game records, and other public information through standardized MCP interfaces, allowing AI assistants to search and analyze chess information.
ChessPal Chess Engine (stockfish) - A Stockfish-powered chess engine exposed as an MCP server. Calculates best moves and supports both HTTP/SSE and stdio transports.
Chroma - Vector database server for semantic document search and metadata filtering, built on Chroma
Claude Thread Continuity - Persistent memory system enabling Claude Desktop conversations to resume with full context across sessions. Maintains conversation history, project states, and user preferences for seamless multi-session workflows.
ClaudePost - ClaudePost enables seamless email management for Gmail, offering secure features like email search, reading, and sending.
ClickUp - MCP server for ClickUp task management, supporting task creation, updates, bulk operations, and markdown descriptions.
Cloudinary - Cloudinary Model Context Protocol Server to upload media to Cloudinary and get back the media link and details.
Coda - Coda.io MCP server from agentr that provides support for reading and writing data to Coda docs and tables.
code-assistant - A coding assistant MCP server that allows to explore a code-base and make changes to code. Should be used with trusted repos only (insufficient protection against prompt injections).
code-executor - An MCP server that allows LLMs to execute Python code within a specified Conda environment.
code-sandbox-mcp - An MCP server to create secure code sandbox environment for executing code within Docker containers.
cognee-mcp - GraphRAG memory server with customizable ingestion, data processing and search
coin_api_mcp - Provides access to coinmarketcap cryptocurrency data.
CoinMarketCap - Implements the complete CoinMarketCap API for accessing cryptocurrency market data, exchange information, and other blockchain-related metrics.
commands - Run commands and scripts. Just like in a terminal.
Computer-Use - Remote MacOS Use - Open-source out-of-the-box alternative to OpenAI Operator, providing a full desktop experience and optimized for using remote macOS machines as autonomous AI agents.
consul-mcp - A consul MCP server for service management, health check and Key-Value Store
Contentful-mcp - Read, update, delete, publish content in your Contentful space(s) from this MCP Server.
context-portal - Context Portal (ConPort) is a memory bank database system that effectively builds a project-specific knowledge graph, capturing entities like decisions, progress, and architecture, along with their relationships. This serves as a powerful backend for Retrieval Augmented Generation (RAG), enabling AI assistants to access precise, up-to-date project information.
CreateveAI Nexus - Open-Source Bridge Between AI Agents and Enterprise Systems, with simple custom API plug-in capabilities (including close compatibility with ComfyUI nodes), support for Copilot Studio’s MCP agent integations, and support for Azure deployment in secure environments with secrets stored in Azure Key Vault, as well as straightforward on-premises deployment.
Creatify - MCP Server that exposes Creatify AI API capabilities for AI video generation, including avatar videos, URL-to-video conversion, text-to-speech, and AI-powered editing tools.
Cronlytic - Create CRUD operations for serverless cron jobs through Cronlytic MCP Server
crypto-feargreed-mcp - Providing real-time and historical Crypto Fear & Greed Index data.
crypto-indicators-mcp - An MCP server providing a range of cryptocurrency technical analysis indicators and strategies.
crypto-sentiment-mcp - An MCP server that delivers cryptocurrency sentiment analysis to AI agents.
cryptopanic-mcp-server - Providing latest cryptocurrency news to AI agents, powered by CryptoPanic.
Cursor MCP Installer - A tool to easily install and configure other MCP servers within Cursor IDE, with support for npm packages, local directories, and Git repositories.
Dappier - Connect LLMs to real-time, rights-cleared, proprietary data from trusted sources. Access specialized models for Real-Time Web Search, News, Sports, Financial Data, Crypto, and premium publisher content. Explore data models at marketplace.dappier.com.
Data Exploration - MCP server for autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort. NOTE: Will execute arbitrary Python code on your machine, please use with caution!
Databricks - Allows LLMs to run SQL queries, list and get details of jobs executions in a Databricks account.
Databricks Genie - A server that connects to the Databricks Genie, allowing LLMs to ask natural language questions, run SQL queries, and interact with Databricks conversational agents.
Databricks Smart SQL - Leveraging Databricks Unity Catalog metadata, perform smart efficient SQL queries to solve Ad-hoc queries and explore data.
Datadog - Datadog MCP Server for application tracing, monitoring, dashboard, incidents queries built on official datadog api.
Dataset Viewer - Browse and analyze Hugging Face datasets with features like search, filtering, statistics, and data export
DataWorks - A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Alibaba Cloud Open API and enables AI agents to perform cloud resources operations seamlessly.
DaVinci Resolve - MCP server integration for DaVinci Resolve providing powerful tools for video editing, color grading, media management, and project control.
DBHub - Universal database MCP server connecting to MySQL, PostgreSQL, SQLite, DuckDB and etc.
Deebo – Agentic debugging MCP server that helps AI coding agents delegate and fix hard bugs through isolated multi-agent hypothesis testing.
Deep Research - Lightweight MCP server offering Grok/OpenAI/Gemini/Perplexity-style automated deep research exploration and structured reporting.
DeepSeek MCP Server - Model Context Protocol server integrating DeepSeek’s advanced language models, in addition to other useful API endpoints
deepseek-thinker-mcp - A MCP (Model Context Protocol) provider Deepseek reasoning content to MCP-enabled AI Clients, like Claude Desktop. Supports access to Deepseek’s thought processes from the Deepseek API service or from a local Ollama server.
Deepseek_R1 - A Model Context Protocol (MCP) server implementation connecting Claude Desktop with DeepSeek’s language models (R1/V3)
Descope - An MCP server to integrate with Descope to search audit logs, manage users, and more.
DesktopCommander - Let AI edit and manage files on your computer, run terminal commands, and connect to remote servers via SSH - all powered by one of the most popular local MCP servers.
DevDb - An MCP server that runs right inside the IDE, for connecting to MySQL, Postgres, SQLite, and MSSQL databases.
Dicom - An MCP server to query and retrieve medical images and for parsing and reading dicom-encapsulated documents (pdf etc.).
Dify - A simple implementation of an MCP server for dify workflows.
Discogs - A MCP server that connects to the Discogs API for interacting with your music collection.
Discord - A MCP server to connect to Discord guilds through a bot and read and write messages in channels
Discord - A MCP server, which connects to Discord through a bot, and provides comprehensive integration with Discord.
Discord - For Discord API integration by Klavis AI
Discourse - A MCP server to search Discourse posts on a Discourse forum.
Docker - Integrate with Docker to manage containers, images, volumes, and networks.
Docs - Enable documentation access for the AI agent, supporting llms.txt and other remote or local files.
Dodo Payments - Enables AI agents to securely perform payment operations via a lightweight, serverless-compatible interface to the Dodo Payments API.
DPLP - Searches the DBLP computer science bibliography database.
Drupal - Server for interacting with Drupal using STDIO transport layer.
dune-analytics-mcp - A mcp server that bridges Dune Analytics data to AI agents.
DynamoDB-Toolbox - Leverages your Schemas and Access Patterns to interact with your DynamoDB Database using natural language.
eBook-mcp - A lightweight MCP server that allows LLMs to read and interact with your personal PDF and EPUB ebooks. Ideal for building AI reading assistants or chat-based ebook interfaces.
EdgeOne Pages MCP - An MCP service for deploying HTML content to EdgeOne Pages and obtaining a publicly accessible URL.
Edwin - MCP server for edwin SDK - enabling AI agents to interact with DeFi protocols across EVM, Solana and other blockchains.
eechat - An open-source, cross-platform desktop application that seamlessly connects with MCP servers, across Linux, macOS, and Windows.
Elasticsearch - MCP server implementation that provides Elasticsearch interaction.
ElevenLabs - A server that integrates with ElevenLabs text-to-speech API capable of generating full voiceovers with multiple voices.
Email - This server enables users to send emails through various email providers, including Gmail, Outlook, Yahoo, Sina, Sohu, 126, 163, and QQ Mail. It also supports attaching files from specified directories, making it easy to upload attachments along with the email content.
Email SMTP - A simple MCP server that lets your AI agent send emails and attach files through SMTP.
Enhance Prompt - An MCP service for enhance you prompt.
Ergo Blockchain MCP -An MCP server to integrate Ergo Blockchain Node and Explorer APIs for checking address balances, analyzing transactions, viewing transaction history, performing forensic analysis of addresses, searching for tokens, and monitoring network status.
Eunomia - Extension of the Eunomia framework that connects Eunomia instruments with MCP servers
Everything Search - Fast file searching capabilities across Windows (using Everything SDK), macOS (using mdfind command), and Linux (using locate/plocate command).
EVM MCP Server - Comprehensive blockchain services for 30+ EVM networks, supporting native tokens, ERC20, NFTs, smart contracts, transactions, and ENS resolution.
Excel - Excel manipulation including data reading/writing, worksheet management, formatting, charts, and pivot table.
Fabric MCP - Microsoft Fabric MCP server to accelerate working in your Fabric Tenant with the help of your favorite LLM models.
fabric-mcp-server - The fabric-mcp-server is an MCP server that integrates Fabric patterns with Cline, exposing them as tools for AI-driven task execution and enhancing Cline’s capabilities.
Facebook Ads - MCP server acting as an interface to the Facebook Ads, enabling programmatic access to Facebook Ads data and management features.
Fantasy PL - Give your coding agent direct access to up-to date Fantasy Premier League data
fastn.ai – Unified API MCP Server - A remote, dynamic MCP server with a unified API that connects to 1,000+ tools, actions, and workflows, featuring built-in authentication and monitoring.
FDIC BankFind MCP Server - (Unofficial) - The is a MCPserver that brings the power of FDIC BankFind APIs straight to your AI tools and workflows. Structured U.S. banking data, delivered with maximum vibes. 😎📊
Federal Reserve Economic Data (FRED) (by Stefano Amorelli) - Community developed MCP server to interact with the Federal Reserve Economic Data.
Fetch - A server that flexibly fetches HTML, JSON, Markdown, or plaintext.
Figma - Give your coding agent direct access to Figma file data, helping it one-shot design implementation.
Fingertip - MCP server for Fingertip.com to search and create new sites.
Firebase - Server to interact with Firebase services including Firebase Authentication, Firestore, and Firebase Storage.
FireCrawl - Advanced web scraping with JavaScript rendering, PDF support, and smart rate limiting
FitBit MCP Server - An MCP server that connects to FitBit API using a token obtained from OAuth flow.
FlightRadar24 - A Claude Desktop MCP server that helps you track flights in real-time using Flightradar24 data.
Flyworks Avatar - Fast and free zeroshot lipsync MCP server.
Foursquare - Enable your agent to recommend places around the world with the Foursquare Places API
freqtrade-mcp - An MCP server that integrates with the Freqtrade cryptocurrency trading bot.
GDB - A GDB/MI protocol server based on the MCP protocol, providing remote application debugging capabilities with AI assistants.
Ghost - A Model Context Protocol (MCP) server for interacting with Ghost CMS through LLM interfaces like Claude.
Git - Allows LLM to interact with a local git repository, incl. optional push support.
Github Actions - A Model Context Protocol (MCP) server for interacting with Github Actions.
GitHub Enterprise MCP - A Model Context Protocol (MCP) server for interacting with GitHub Enterprise.
GitMCP - gitmcp.io is a generic remote MCP server to connect to ANY GitHub repository or project documentation effortlessly
Glean - A server that uses Glean API to search and chat.
Gmail - A Model Context Protocol (MCP) server for Gmail integration in Claude Desktop with auto authentication support.
Gmail Headless - Remote hostable MCP server that can get and send Gmail messages without local credential or file system setup.
Gnuradio - An MCP server for GNU Radio that enables LLMs to autonomously create and modify RF .grc flowcharts.
Goal Story - a Goal Tracker and Visualization Tool for personal and professional development.
GOAT - Run more than +200 onchain actions on any blockchain including Ethereum, Solana and Base.
Godot - A MCP server providing comprehensive Godot engine integration for project editing, debugging, and scene management.
Golang Filesystem Server - Secure file operations with configurable access controls built with Go!
Goodnews - A simple MCP server that delivers curated positive and uplifting news stories.
Google Analytics - Google Analytics MCP Server to bring data across 200+ dimensions & metrics for LLMs to analyse.
Google Calendar - Integration with Google Calendar to check schedules, find time, and add/delete events
Google Calendar - Google Calendar MCP Server for managing Google calendar events. Also supports searching for events by attributes like title and location.
Google Custom Search - Provides Google Search results via the Google Custom Search API
Google Sheets - Access and editing data to your Google Sheets.
Google Sheets - A MCP Server written in TypeScript to access and edit data in your Google Sheets.
Google Tasks - Google Tasks API Model Context Protocol Server.
Google Vertex AI Search - Provides Google Vertex AI Search results by grounding a Gemini model with your own private data
Google Workspace - Comprehensive Google Workspace MCP with full support for Calendar, Drive, Gmail, and Docs using Streamable HTTP or SSE transport.
GraphQL - Comprehensive GraphQL API integration that automatically exposes each GraphQL query as a separate tool.
GraphQL Schema - Allow LLMs to explore large GraphQL schemas without bloating the context.
Hashing MCP Server - MCP Server with cryptographic hashing functions e.g. SHA256, MD5, etc.
HDW LinkedIn - Access to profile data and management of user account with HorizonDataWave.ai.
Helm Chart CLI - Helm MCP provides a bridge between AI assistants and the Helm package manager for Kubernetes. It allows AI assistants to interact with Helm through natural language requests, executing commands like installing charts, managing repositories, and more.
Heurist Mesh Agent - Access specialized web3 AI agents for blockchain analysis, smart contract security, token metrics, and blockchain interactions through the Heurist Mesh network.
Holaspirit - Interact with Holaspirit.
Home Assistant - Interact with Home Assistant including viewing and controlling lights, switches, sensors, and all other Home Assistant entities.
Home Assistant - Docker-ready MCP server for Home Assistant with entity management, domain summaries, automation support, and guided conversations. Includes pre-built container images for easy installation.
HubSpot - HubSpot CRM integration for managing contacts and companies. Create and retrieve CRM data directly through Claude chat.
HuggingFace Spaces - Server for using HuggingFace Spaces, supporting Open Source Image, Audio, Text Models and more. Claude Desktop mode for easy integration.
Human-In-the-Loop - A powerful MCP Server that enables AI assistants like Claude to interact with humans through intuitive GUI dialogs. This server bridges the gap between automated AI processes and human decision-making by providing real-time user input tools, choices, confirmations, and feedback mechanisms.
Human-use - Instant human feedback through an MCP, have your AI interact with humans around the world. Powered by Rapidata
Hyperliquid - An MCP server implementation that integrates the Hyperliquid SDK for exchange data.
hyprmcp (by Stefano Amorelli) - Lightweight MCP server for hyprland.
iFlytek SparkAgent Platform - This is a simple example of using MCP Server to invoke the task chain of the iFlytek SparkAgent Platform.
iFlytek Workflow - Connect to iFlytek Workflow via the MCP server and run your own Agent.
Image Generation - This MCP server provides image generation capabilities using the Replicate Flux model.
iMCP - A macOS app that provides an MCP server for your iMessage, Reminders, and other Apple services.
InfluxDB - Run queries against InfluxDB OSS API v2.
Inoyu - Interact with an Apache Unomi CDP customer data platform to retrieve and update customer profiles
interactive-mcp - Enables interactive LLM workflows by adding local user prompts and chat capabilities directly into the MCP loop.
Intercom - An MCP-compliant server for retrieving customer support tickets from Intercom. This tool enables AI assistants like Claude Desktop and Cline to access and analyze your Intercom support tickets.
iOS Simulator - A Model Context Protocol (MCP) server that enables LLMs to interact with iOS simulators (iPhone, iPad, etc.) through natural language commands.
iTerm MCP - Integration with iTerm2 terminal emulator for macOS, enabling LLMs to execute and monitor terminal commands.
iTerm MCP Server - A Model Context Protocol (MCP) server implementation for iTerm2 terminal integration. Able to manage multiple iTerm Sessions.
Java Decompiler - Decompile Java bytecode into readable source code from .class files, package names, or JAR archives using CFR decompiler
JavaFX - Make drawings using a JavaFX canvas
JavaFX - Make drawings using a JavaFX canvas
JDBC - Connect to any JDBC-compatible database and query, insert, update, delete, and more. Supports MySQL, PostgreSQL, Oracle, SQL Server, sqllite and more.
JMeter - Run load testing using Apache JMeter via MCP-compliant tools.
Job Searcher - A FastMCP server that provides tools for retrieving and filtering job listings based on time period, keywords, and remote work preferences.
jobswithgpt - Job search MCP using jobswithgpt which indexes 500K+ public job listings and refreshed continously.
JSON - JSON handling and processing server with advanced query capabilities using JSONPath syntax and support for array, string, numeric, and date operations.
JSON2Video MCP - A Model Context Protocol (MCP) server implementation for programmatically generating videos using the json2video API. This server exposes powerful video generation and status-checking tools for use with LLMs, agents, or any MCP-compatible client.
jupiter-mcp - An MCP server for executing token swaps on the Solana blockchain using Jupiter’s new Ultra API.
Jupyter Notebook - connects Jupyter Notebook to Claude AI, allowing Claude to directly interact with and control Jupyter Notebooks. This integration enables AI-assisted code execution, data analysis, visualization, and more.
k8s-multicluster-mcp - An MCP server for interact with multiple Kubernetes clusters simultaneously using multiple kubeconfig files.
Keycloak MCP - This MCP server enables natural language interaction with Keycloak for user and realm management including creating, deleting, and listing users and realms.
Kibana MCP (by TocharianOU) - A community-maintained MCP server implementation that allows any MCP-compatible client to access and manage Kibana instances through natural language or programmatic requests.
Kibela (by kiwamizamurai) - Interact with Kibela API.
KiCad MCP - MCP server for KiCad on Mac, Windows, and Linux.
kintone - Manage records and apps in kintone through LLM tools.
Kokoro TTS - Use Kokoro text to speech to convert text to MP3s with optional autoupload to S3.
Kong Konnect - A Model Context Protocol (MCP) server for interacting with Kong Konnect APIs, allowing AI assistants to query and analyze Kong Gateway configurations, traffic, and analytics.
Kubernetes - Connect to Kubernetes cluster and manage pods, deployments, and services.
Kubernetes and OpenShift - A powerful Kubernetes MCP server with additional support for OpenShift. Besides providing CRUD operations for any Kubernetes resource, this server provides specialized tools to interact with your cluster.
KubeSphere - The KubeSphere MCP Server is a Model Context Protocol(MCP) server that provides integration with KubeSphere APIs, enabling to get resources from KubeSphere. Divided into four tools modules: Workspace Management, Cluster Management, User and Roles, Extensions Center.
Langflow-DOC-QA-SERVER - A Model Context Protocol server for document Q&A powered by Langflow. It demonstrates core MCP concepts by providing a simple interface to query documents through a Langflow backend.
Lark(Feishu) - A Model Context Protocol(MCP) server for Lark(Feishu) sheet, message, doc and etc.
lean-lsp-mcp - Interact with the Lean theorem prover via the Language Server Protocol.
Lightdash - Interact with Lightdash, a BI tool.
LINE (by amornpan) - Implementation for LINE Bot integration that enables Language Models to read and analyze LINE conversations through a standardized interface. Features asynchronous operation, comprehensive logging, webhook event handling, and support for various message types.
Linear - Interact with Linear project management system.
Linear - Allows LLM to interact with Linear’s API for project management, including searching, creating, and updating issues.
Linear (Go) - Allows LLM to interact with Linear’s API via a single static binary.
Linear MCP - Full blown implementation of the Linear SDK to support comprehensive Linear management of projects, initiatives, issues, users, teams and states.
LlamaCloud (by marcusschiesser) - Integrate the data stored in a managed index on LlamaCloud
lldb-mcp - A Model Context Protocol server for LLDB that provides LLM-driven debugging.
llm-context - Provides a repo-packing MCP tool with configurable profiles that specify file inclusion/exclusion patterns and optional prompts.
Loki - Golang based MCP Server to query logs from Grafana Loki.
LottieFiles - Searching and retrieving Lottie animations from LottieFiles
lsp-mcp - Interact with Language Servers usint the Language Server Protocol to provide additional context information via hover, code actions and completions.
Lspace - Turn scattered ChatGPT/Claude/Cursor conversations into persistent, searchable knowledge.
lucene-mcp-server - spring boot server using Lucene for fast document search and management.
mac-messages-mcp - An MCP server that securely interfaces with your iMessage database via the Model Context Protocol (MCP), allowing LLMs to query and analyze iMessage conversations. It includes robust phone number validation, attachment processing, contact management, group chat handling, and full support for sending and receiving messages.
Maestro MCP - An MCP server for interacting with Bitcoin via the Maestro RPC API.
MalwareBazaar_MCP (by Kevin Thomas) - An AI-driven MCP server that autonomously interfaces with MalwareBazaar, delivering real-time threat intel and sample metadata for authorized cybersecurity research workflows.
MariaDB - MariaDB database integration with configurable access controls in Python.
Markdown2doc - Convert between various file formats using Pandoc
Markdownify - MCP to convert almost anything to Markdown (PPTX, HTML, PDF, Youtube Transcripts and more)
Markitdown - Convert files to Markdown
MasterGo - The server designed to connect MasterGo design tools with AI models. It enables AI models to directly retrieve DSL data from MasterGo design files.
Matlab-MCP-Tools - An MCP to write and execute MATLAB scripts, maintain workspace context between MCP calls, visualize plots, and perform section-by-section analysis of MATLAB code with full access to MATLAB’s computational capabilities.
Maton - Connect to your SaaS tools like HubSpot, Salesforce, and more.
MCP Compass - Suggest the right MCP server for your needs
MCP Create - A dynamic MCP server management service that creates, runs, and manages Model Context Protocol servers on-the-fly.
MCP Installer - This server is a server that installs other MCP servers for you.
MCP Proxy Server - An MCP proxy server that aggregates and serves multiple MCP resource servers through a single HTTP server.
MCP Server Creator - A powerful Model Context Protocol (MCP) server that creates other MCP servers! This meta-server provides tools for dynamically generating FastMCP server configurations and Python code.
MCP STDIO to Streamable HTTP Adapter - Connect to Streamable HTTP MCP Servers even if the MCP Client only supports STDIO.
mcp-containerd - The containerd MCP implemented by Rust supports the operation of the CRI interface.
MCP-Database-Server - Fastest way to interact with your Database such as SQL Server, SQLite and PostgreSQL
mcp-grep - Python-based MCP server that brings grep functionality to LLMs. Supports common grep features including pattern searching, case-insensitive matching, context lines, and recursive directory searches.
mcp-k8s-go - Golang-based Kubernetes server for MCP to browse pods and their logs, events, namespaces and more. Built to be extensible.
mcp-local-rag - “primitive” RAG-like web search model context protocol (MCP) server that runs locally using Google’s MediaPipe Text Embedder and DuckDuckGo Search.
mcp-meme-sticky - Make memes or stickers using MCP server for WhatsApp or Telegram.
MCP-NixOS - A Model Context Protocol server that provides AI assistants with accurate, real-time information about NixOS packages, system options, Home Manager settings, and nix-darwin macOS configurations.
mcp-open-library - A Model Context Protocol (MCP) server for the Open Library API that enables AI assistants to search for book and author information.
mcp-proxy - Connect to MCP servers that run on SSE transport, or expose stdio servers as an SSE server.
mcp-salesforce - MCP server with basic demonstration of interactions with your Salesforce instance
mcp-sanctions - Screen individuals and organizations against global sanctions lists (OFAC, SDN, UN, etc). Query by prompt or document upload.
mcp-server-leetcode - Practice and retrieve problems from LeetCode. Automate problem retrieval, solutions, and insights for coding practice and competitions.
mcp-vision - A MCP server exposing HuggingFace computer vision models such as zero-shot object detection as tools, enhancing the vision capabilities of large language or vision-language models.
mcp-weather - Accurate weather forecasts via the AccuWeather API (free tier available).
mcp_weather - Get weather information from https://api.open-meteo.com API.
MCPIgnore Filesytem - A Data Security First filesystem MCP server that implements .mcpignore to prevent MCP clients from accessing sensitive data.
MediaWiki MCP adapter - A custom Model Context Protocol adapter for MediaWiki and WikiBase APIs
mem0-mcp - A Model Context Protocol server for Mem0, which helps with managing coding preferences.
Membase - Save and query your agent memory in distributed way by Membase.
MetaTrader MCP - Enable AI LLMs to execute trades using MetaTrader 5 platform.
Metricool MCP - A Model Context Protocol server that integrates with Metricool’s social media analytics platform to retrieve performance metrics and schedule content across networks like Instagram, Facebook, Twitter, LinkedIn, TikTok and YouTube.
Microsoft 365 - (by Merill) A Model Context Protocol (MCP) server for Microsoft 365. Includes support for all services including Teams, SharePoint, Exchange, OneDrive, Entra, Intune and more. See Lokka for more details.
Microsoft 365 - MCP server that connects to Microsoft Office and the whole Microsoft 365 suite using Graph API (including Outlook/mail, files, Excel, calendar)
Microsoft Teams - MCP server that integrates Microsoft Teams messaging (read, post, mention, list members and threads)
Mifos X - A MCP server for the Mifos X Open Source Banking useful for managing clients, loans, savings, shares, financial transactions and generating financial reports.
Mikrotik - Mikrotik MCP server which cover networking operations (IP, DHCP, Firewall, etc)
Mindmap (by YuChenSSR) - A server that generates mindmaps from input containing markdown code.
Minima - MCP server for RAG on local files
Mobile MCP (by Mobile Next) - MCP server for Mobile(iOS/Android) automation, app scraping and development using physical devices or simulators/emulators.
Monday.com - MCP Server to interact with Monday.com boards and items.
MongoDB - A Model Context Protocol Server for MongoDB.
MongoDB & Mongoose - MongoDB MCP Server with Mongoose Schema and Validation.
MongoDB Lens - Full Featured MCP Server for MongoDB Databases.
Monzo - Access and manage your Monzo bank accounts through natural language, including balance checking, pot management, transaction listing, and transaction annotation across multiple account types (personal, joint, flex).
Morningstar - MCP Server to interact with Morningstar Research, Editorial and Datapoints
MSSQL - MSSQL database integration with configurable access controls and schema inspection
MSSQL (by jexin) - MCP Server for MSSQL database in Python
MSSQL-MCP (by daobataotie) - MSSQL MCP that refer to the official website’s SQLite MCP for modifications to adapt to MSSQL
MSSQL-Python (by amornpan) - A read-only Python implementation for MSSQL database access with enhanced security features, configurable access controls, and schema inspection capabilities. Focuses on safe database interaction through Python ecosystem.
Multi-Model Advisor - A Model Context Protocol (MCP) server that orchestrates queries across multiple Ollama models, synthesizing their insights to deliver a comprehensive and multifaceted AI perspective on any given query.
Multicluster-MCP-Sever - The gateway for GenAI systems to interact with multiple Kubernetes clusters.
MySQL (by benborla) - MySQL database integration in NodeJS with configurable access controls and schema inspection
MySQL (by DesignComputer) - MySQL database integration in Python with configurable access controls and schema inspection
n8n - This MCP server provides tools and resources for AI assistants to manage n8n workflows and executions, including listing, creating, updating, and deleting workflows, as well as monitoring their execution status.
Nacos MCP Router - This MCP(Model Context Protocol) Server provides tools to search, install, proxy other MCP servers.
NASA (by ProgramComputer) - Access to a unified gateway of NASA’s data sources including but not limited to APOD, NEO, EPIC, GIBS.
Nasdaq Data Link (by stefanoamorelli) - An MCP server to access, explore, and interact with Nasdaq Data Link’s extensive and valuable financial and economic datasets.
National Parks - The server provides latest information of park details, alerts, visitor centers, campgrounds, hiking trails, and events for U.S. National Parks.
NAVER (by pfldy2850) - This MCP server provides tools to interact with various Naver services, such as searching blogs, news, books, and more.
NBA - This MCP server provides tools to fetch recent and historical NBA games including basic and advanced statistics.
Neo4j - A community built server that interacts with Neo4j Graph Database.
Neovim - An MCP Server for your Neovim session.
Netbird - List and analyze Netbird network peers, groups, policies, and more.
NocoDB - Read and write access to NocoDB database.
nomad-mcp - A server that provides a set of tools for managing Nomad clusters through the MCP.
Notion (by suekou) - Interact with Notion API.
Notion (by v-3) - Notion MCP integration. Search, Read, Update, and Create pages through Claude chat.
NS Travel Information - Access Dutch Railways (NS) real-time train travel information and disruptions through the official NS API.
ntfy-mcp (by teddyzxcv) - The MCP server that keeps you informed by sending the notification on phone using ntfy
ntfy-me-mcp (by gitmotion) - An ntfy MCP server for sending/fetching ntfy notifications to your self-hosted ntfy server from AI Agents 📤 (supports secure token auth & more - use with npx or docker!)
oatpp-mcp - C++ MCP integration for Oat++. Use Oat++ to build MCP servers.
Obsidian Markdown Notes - Read and search through your Obsidian vault or any directory containing Markdown notes
obsidian-mcp - (by Steven Stavrakis) An MCP server for Obsidian.md with tools for searching, reading, writing, and organizing notes.
OceanBase - (by yuanoOo) A Model Context Protocol (MCP) server that enables secure interaction with OceanBase databases.
Office-PowerPoint-MCP-Server - A Model Context Protocol (MCP) server for creating, reading, and manipulating Microsoft PowerPoint documents.
Office-Visio-MCP-Server - A Model Context Protocol (MCP) server for creating, reading, and manipulating Microsoft Visio documents.
Office-Word-MCP-Server - A Model Context Protocol (MCP) server for creating, reading, and manipulating Microsoft Word documents.
Okta - Interact with Okta API.
OneNote - (by Rajesh Vijay) An MCP server that connects to Microsoft OneNote using the Microsoft Graph API. Reading notebooks, sections, and pages from OneNote,Creating new notebooks, sections, and pages in OneNote.
Open Strategy Partners Marketing Tools - Content editing codes, value map, and positioning tools for product marketing.
OpenAI WebSearch MCP - This is a Python-based MCP server that provides OpenAI web_search build-in tool.
OpenAPI - Interact with OpenAPI APIs.
OpenAPI AnyApi - Interact with large OpenAPI docs using built-in semantic search for endpoints. Allows for customizing the MCP server prefix.
OpenAPI Schema - Allow LLMs to explore large OpenAPI schemas without bloating the context.
OpenAPI Schema Explorer - Token-efficient access to local or remote OpenAPI/Swagger specs via MCP Resources.
OpenCTI - Interact with OpenCTI platform to retrieve threat intelligence data including reports, indicators, malware and threat actors.
OpenCV - A MCP server providing OpenCV computer vision capabilities. This allows AI assistants and language models to access powerful computer vision tools.
OpenDota - Interact with OpenDota API to retrieve Dota 2 match data, player statistics, and more.
OpenRPC - Interact with and discover JSON-RPC APIs via OpenRPC.
OpenWeather - Interact with the free openweathermap API to get the current and forecast weather for a location.
Oura Ring (by Rajesh Vijay) - MCP Server to access and analyze your Oura Ring data. It provides a structured way to fetch and understand your health metrics.
Outline - MCP Server to interact with Outline knowledge base to search, read, create, and manage documents and their content, access collections, add comments, and manage document backlinks.
pancakeswap-poolspy-mcp - An MCP server that tracks newly created liquidity pools on Pancake Swap.
Pandoc - MCP server for seamless document format conversion using Pandoc, supporting Markdown, HTML, PDF, DOCX (.docx), csv and more.
Paradex MCP - MCP native server for interacting with Paradex platform, including fully features trading.
Peacock for VS Code - MCP Server for the Peacock extension for VS Code, coloring your world, one Code editor at a time. The main goal of the project is to show how an MCP server can be used to interact with APIs.
Phone MCP - 📱 A powerful plugin that lets you control your Android phone. Enables AI agents to perform complex tasks like automatically playing music based on weather or making calls and sending texts.
PIF - A Personal Intelligence Framework (PIF), providing tools for file operations, structured reasoning, and journal-based documentation to support continuity and evolving human-AI collaboration across sessions.
Pinecone - MCP server for searching and uploading records to Pinecone. Allows for simple RAG features, leveraging Pinecone’s Inference API.
Pinner MCP - A MCP server for pinning GitHub Actions and container base images to their immutable SHA hashes to prevent supply chain attacks.
Placid.app - Generate image and video creatives using Placid.app templates
Plane - This MCP Server will help you to manage projects and issues through Plane’s API
Playwright - This MCP Server will help you run browser automation and webscraping using Playwright
Postman - MCP server for running Postman Collections locally via Newman. Allows for simple execution of Postman Server and returns the results of whether the collection passed all the tests.
Prefect - MCP Server for workflow orchestration and ELT/ETL with Prefect Server, and Prefect Cloud [https://www.prefect.io/] using the prefect python client.
Productboard - Integrate the Productboard API into agentic workflows via MCP.
Prometheus - Query and analyze Prometheus - open-source monitoring system.
PubChem - extract drug information from pubchem API.
Pulumi - MCP Server to Interact with Pulumi API, creates and lists Stacks
Puppeteer vision - Use Puppeteer to browse a webpage and return a high quality Markdown. Use AI vision capabilities to handle cookies, captchas, and other interactive elements automatically.
Pushover - Send instant notifications to your devices using Pushover.net
pydantic/pydantic-ai/mcp-run-python - Run Python code in a secure sandbox via MCP tool calls, powered by Deno and Pyodide
QGIS - connects QGIS to Claude AI through the MCP. This integration enables prompt-assisted project creation, layer loading, code execution, and more.
Qiniu MCP Server - The Model Context Protocol (MCP) Server built on Qiniu Cloud products supports users in accessing Qiniu Cloud Storage, intelligent multimedia services, and more through this MCP Server within the context of AI large model clients.
Quarkus - MCP servers for the Quarkus Java framework.
QuickChart - A Model Context Protocol server for generating charts using QuickChart.io
Qwen_Max - A Model Context Protocol (MCP) server implementation for the Qwen models.
RabbitMQ - The MCP server that interacts with RabbitMQ to publish and consume messages.
RAG Local - This MCP server for storing and retrieving text passages locally based on their semantic meaning.
RAG Web Browser An MCP server for Apify’s open-source RAG Web Browser Actor to perform web searches, scrape URLs, and return content in Markdown.
Raindrop.io - An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP).
Reaper - Interact with your Reaper (Digital Audio Workstation) projects.
Redis - Redis database operations and caching microservice server with support for key-value operations, expiration management, and pattern-based key listing.
Redis MCP server to interact with Redis Server, AWS Memory DB, etc for caching or other use-cases where in-memory and key-value based storage is appropriate
RedNote MCP - MCP server for accessing RedNote(XiaoHongShu, xhs) content
Reed Jobs - Search and retrieve job listings from Reed.co.uk.
Rememberizer AI - An MCP server designed for interacting with the Rememberizer data source, facilitating enhanced knowledge retrieval.
Replicate - Search, run and manage machine learning models on Replicate through a simple tool-based interface. Browse models, create predictions, track their status, and handle generated images.
Resend - Send email using Resend services
Rijksmuseum - Interface with the Rijksmuseum API to search artworks, retrieve artwork details, access image tiles, and explore user collections.
Riot Games - MCP server for League of Legends – fetch player info, ranks, champion stats, and match history via Riot API.
Rquest - An MCP server providing realistic browser-like HTTP request capabilities with accurate TLS/JA3/JA4 fingerprints for bypassing anti-bot measures.
Rust MCP Filesystem - Fast, asynchronous MCP server for efficient handling of various filesystem operations built with the power of Rust.
Salesforce MCP - Salesforce MCP server. Supports cloud version Salesforce-mcp.com and allows both data & metadata functions.
Salesforce MCP - Interact with Salesforce Data and Metadata
Salesforce MCP Server - Comprehensive Salesforce integration with tools for querying records, executing Apex, managing fields/objects, and handling debug logs
Scholarly - A MCP server to search for scholarly and academic articles.
scrapling-fetch - Access text content from bot-protected websites. Fetches HTML/markdown from sites with anti-automation measures using Scrapling.
SearXNG - A Model Context Protocol Server for SearXNG
SearXNG - A MCP server provide web searching via SearXNG & retrieve url as makrdown.
SearXNG Public - A Model Context Protocol Server for retrieving data from public SearXNG instances, with fallback support
SEC EDGAR - (by Stefano Amorelli) A community Model Context Protocol Server to access financial filings and data through the U.S. Securities and Exchange Commission (SEC) Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database
Serper - An MCP server that performs Google searches using Serper.
ServiceNow - A MCP server to interact with a ServiceNow instance
ShaderToy - This MCP server lets LLMs to interact with the ShaderToy API, allowing LLMs to learn from compute shaders examples and enabling them to create complex GLSL shaders that they are previously not capable of.
Shodan MCP - MCP server to interact with Shodan
Shopify - MCP to interact with Shopify API including order, product, customers and so on.
Simple Loki MCP - A simple MCP server to query Loki logs using logcli.
Siri Shortcuts - MCP to interact with Siri Shortcuts on macOS. Exposes all Shortcuts as MCP tools.
Skyvern - MCP to let Claude / Windsurf / Cursor / your LLM control the browser
Slack - The most powerful MCP server for Slack Workspaces. This integration supports both Stdio and SSE transports, proxy settings and does not require any permissions or bots being created or approved by Workspace admins 😏.
Slidespeak - Create PowerPoint presentations using the Slidespeak API.
Smartlead - MCP to connect to Smartlead. Additional, tooling, functionality, and connection to workflow automation platforms also available.
Snowflake - This MCP server enables LLMs to interact with Snowflake databases, allowing for secure and controlled data operations.
SoccerDataAPI - This MCP server provides real-time football match data based on the SoccerDataAPI.
Solana Agent Kit - This MCP server enables LLMs to interact with the Solana blockchain with help of Solana Agent Kit by SendAI, allowing for 40+ protcool actions and growing
Solr MCP - This MCP server offers a basic functionality to perform a search on Solr servers.
Solver - Solves constraint satisfaction and optimization problems .
Splunk - Golang MCP server for Splunk (lists saved searches, alerts, indexes, macros…). Supports SSE and STDIO.
Spotify - This MCP allows an LLM to play and use Spotify.
Spring Initializr - This MCP allows an LLM to create Spring Boot projects with custom configurations. Instead of manually visiting start.spring.io, you can now ask your AI assistant to generate projects with specific dependencies, Java versions, and project structures.
SSH - Agent for managing and controlling SSH connections.
SSH - An MCP server that can execute SSH commands remotely, upload files, download files, and so on.
Standard Korean Dictionary - Search the dictionary using API
Star Wars -MCP Server for the SWAPI Star Wars API. The main goal of the project is to show how an MCP server can be used to interact with APIs.
Starknet MCP Server - A comprehensive MCP server for interacting with the Starknet blockchain, providing tools for querying blockchain data, resolving StarknetIDs, and performing token transfers.
Starwind UI - This MCP provides relevant commands, documentation, and other information to allow LLMs to take full advantage of Starwind UI’s open source Astro components.
Stitch AI - Knowledge management system for AI agents with memory space creation and retrieval capabilities.
Strava - Connect to the Strava API to access activity data, athlete profiles, segments, and routes, enabling fitness tracking and analysis with Claude.
Stripe - This MCP allows integration with Stripe for handling payments, customers, and refunds.
Substack/Medium - Connect Claude to your Substack/Medium writing, enabling semantic search and analysis of your published content.
System Health - The MCP (Multi-Channel Protocol) System Health Monitoring is a robust, real-time monitoring solution designed to provide comprehensive health metrics and alerts for remote Linux servers.
Talk To Figma - This MCP server enables LLMs to interact with Figma, allowing them to read and modify designs programmatically.
Tavily search - An MCP server for Tavily’s search & news API, with explicit site inclusions/exclusions
TeamRetro - This MCP server allows LLMs to interact with TeamRetro, allowing LLMs to manage user, team, team member, retrospective, health check, action, agreement and fetch the reports.
Telegram - An MCP server that provides paginated chat reading, message retrieval, and message sending capabilities for Telegram through Telethon integration.
Telegram-Client - A Telegram API bridge that manages user data, dialogs, messages, drafts, read status, and more for seamless interactions.
Tempo - An MCP server to query traces/spans from Grafana Tempo.
Teradata - his MCP server enables LLMs to interact with Teradata databases. This MCP Server support tools and prompts for multi task data analytics
Terminal-Control - A MCP server that enables secure terminal command execution, directory navigation, and file system operations through a standardized interface.
Terraform-Cloud - An MCP server that integrates AI assistants with the Terraform Cloud API, allowing you to manage your infrastructure through natural conversation.
TFT-Match-Analyzer - MCP server for teamfight tactics match history & match details fetching, providing user the detailed context for every match.
thegraph-mcp - An MCP server that powers AI agents with indexed blockchain data from The Graph.
Things3 MCP - Things3 task management integration for macOS with comprehensive TODO, project, and tag management.
Think MCP - Enhances any agent’s reasoning capabilities by integrating the think-tools, as described in Anthropic’s article.
Ticketmaster - Search for events, venues, and attractions through the Ticketmaster Discovery API
TickTick - A Model Context Protocol (MCP) server designed to integrate with the TickTick task management platform, enabling intelligent context-aware task operations and automation.
TMDB - This MCP server integrates with The Movie Database (TMDB) API to provide movie information, search capabilities, and recommendations.
Todoist - Interact with Todoist to manage your tasks.
Todos - A practical todo list manager to use with your favourite chatbot.
token-minter-mcp - An MCP server providing tools for AI agents to mint ERC-20 tokens across multiple blockchains.
token-revoke-mcp - An MCP server for checking and revoking ERC-20 token allowances across multiple blockchains.
Ton Blockchain MCP - An MCP server for interacting with Ton Blockchain.
TouchDesigner - An MCP server for TouchDesigner, enabling interaction with TouchDesigner projects, nodes, and parameters.
Travel Planner - Travel planning and itinerary management server integrating with Google Maps API for location search, place details, and route calculations.
Trello MCP Server - An MCP server that interact with user Trello boards, modifying them with prompting.
Tripadvisor - A MCP server that enables LLMs to interact with Tripadvisor API, supporting location data, reviews, and photos through standardized MCP interfaces
Tsuki-Mcp-Filesystem-Server - A simple, fast, and fully MCP-compliant server for listing local filesystem files. Built with Python + FastAPI. Designed for OpenAI’s Agent SDK via resources/list.
Tyk API Management - Chat with all of your organization’s managed APIs and perform other API lifecycle operations, managing tokens, users, analytics, and more.
Typesense - A Model Context Protocol (MCP) server implementation that provides AI models with access to Typesense search capabilities. This server enables LLMs to discover, search, and analyze data stored in Typesense collections.
uniswap-poolspy-mcp - An MCP server that tracks newly created liquidity pools on Uniswap across nine blockchain networks.
uniswap-trader-mcp -An MCP server for AI agents to automate token swaps on Uniswap DEX across multiple blockchains.
Unity Catalog - An MCP server that enables LLMs to interact with Unity Catalog AI, supporting CRUD operations on Unity Catalog Functions and executing them as MCP tools.
Unity Integration (Advanced) - Advanced Unity3d Game Engine MCP which supports ,Execution of Any Editor Related Code Directly Inside of Unity, Fetch Logs, Get Editor State and Allow File Access of the Project making it much more useful in Script Editing or asset creation.
Unity3d Game Engine - An MCP server that enables LLMs to interact with Unity3d Game Engine, supporting access to a variety of the Unit’s Editor engine tools (e.g. Console Logs, Test Runner logs, Editor functions, hierarchy state, etc) and executing them as MCP tools or gather them as resources.
Unleash Integration (Feature Toggle) - A Model Context Protocol (MCP) server implementation that integrates with Unleash Feature Toggle system. Provide a bridge between LLM applications and Unleash feature flag system
User Feedback - Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor.
USPTO - MCP server for accessing United States Patent & Trademark Office data through its Open Data Protocol (ODP) API.
Vectara - Query Vectara’s trusted RAG-as-a-service platform.
Vega-Lite - Generate visualizations from fetched data using the VegaLite format and renderer.
Vertica - Vertica database integration in Python with configurable access controls and schema inspection
Vibe Check - An MCP server leveraging an external oversight layer to “vibe check” agents, and also self-improve accuracy & user alignment over time. Prevents scope creep, code bloat, misalignment, misinterpretation, tunnel vision, and overcomplication.
Video Editor - A Model Context Protocol Server to add, edit, and search videos with Video Jungle.
Video Still Capture - 📷 Capture video stills from an OpenCV-compatible webcam or other video source.
Virtual location (Google Street View,etc.) - Integrates Google Map, Google Street View, PixAI, Stability.ai, ComfyUI API and Bluesky to provide a virtual location simulation in LLM (written in Effect.ts)
VolcEngine TOS - A sample MCP server for VolcEngine TOS that flexibly get objects from TOS.
Voyp - VOYP MCP server for making calls using Artificial Intelligence.
Wanaku MCP Router - The Wanaku MCP Router is a SSE-based MCP server that provides an extensible routing engine that allows integrating your enterprise systems with AI agents.
weather-mcp-server - Get real-time weather data for any location using weatherapi.
Webflow - Interfact with the Webflow APIs
whale-tracker-mcp - A mcp server for tracking cryptocurrency whale transactions.
WhatsApp MCP Server - MCP server for your personal WhatsApp handling individuals, groups, searching and sending.
Whois MCP - MCP server that performs whois lookup against domain, IP, ASN and TLD.
Wikidata MCP - Wikidata MCP server that interact with Wikidata, by searching identifiers, extracting metadata, and executing sparql query.
WildFly MCP - WildFly MCP server that enables LLM to interact with running WildFly servers (retrieve metrics, logs, invoke operations, …).
Windows CLI - MCP server for secure command-line interactions on Windows systems, enabling controlled access to PowerShell, CMD, and Git Bash shells.
Workflowy - A server that interacts with workflowy.
World Bank data API - A server that fetches data indicators available with the World Bank as part of their data API
Wren Engine - The Semantic Engine for Model Context Protocol(MCP) Clients and AI Agents
X (Twitter) (by EnesCinr) - Interact with twitter API. Post tweets and search for tweets by query.
X (Twitter) (by vidhupv) - Create, manage and publish X/Twitter posts directly through Claude chat.
Xcode - MCP server that brings AI to your Xcode projects, enabling intelligent code assistance, file operations, project management, and automated development tasks.
xcodebuild - 🍎 Build iOS Xcode workspace/project and feed back errors to llm.
Xero-mcp-server - Enabling clients to interact with Xero system for streamlined accounting, invoicing, and business operations.
XiYan - 🗄️ An MCP server that supports fetching data from a database using natural language queries, powered by XiyanSQL as the text-to-SQL LLM.
XMind - Read and search through your XMind directory containing XMind files.
yfinance -💹The MCP YFinance Stock Server provides real-time and historical stock data in a standard format, powering dashboards, AI agents,and research tools with seamless financial insights.
YNAB - A Model Context Protocol (MCP) server for integrating with YNAB (You Need A Budget), allowing AI assistants to securely access and analyze your financial data.
YouTube - Extract Youtube video information (with proxies support).
YouTube - Comprehensive YouTube API integration for video management, Shorts creation, and analytics.
YouTube Video Summarizer - Summarize lengthy youtube videos.
Zoom - Create, update, read and delete your zoom meetings.

📚 Frameworks

These are high-level frameworks that make it easier to build MCP servers or clients.

For servers

EasyMCP (TypeScript)

FastAPI to MCP auto generator – A zero-configuration tool for automatically exposing FastAPI endpoints as MCP tools by Tadata

FastMCP (TypeScript)
Foxy Contexts – A library to build MCP servers in Golang by strowk
Higress MCP Server Hosting - A solution for hosting MCP Servers by extending the API Gateway (based on Envoy) with wasm plugins.
MCP-Framework Build MCP servers with elegance and speed in Typescript. Comes with a CLI to create your project with mcp create app. Get started with your first server in under 5 minutes by Alex Andru
Quarkus MCP Server SDK (Java)
Spring AI MCP Server - Provides auto-configuration for setting up an MCP server in Spring Boot applications.
Template MCP Server - A CLI tool to create a new Model Context Protocol server project with TypeScript support, dual transport options, and an extensible structure

For clients

codemirror-mcp - CodeMirror extension that implements the Model Context Protocol (MCP) for resource mentions and prompt commands
Spring AI MCP Client - Provides auto-configuration for MCP client functionality in Spring Boot applications.

📚 Resources

Additional resources on MCP.

AiMCP - A collection of MCP clients&servers to find the right mcp tools by Hekmon
Awesome Crypto MCP Servers by badkk - A curated list of MCP servers by Luke Fan
Awesome MCP Servers by appcypher - A curated list of MCP servers by Stephen Akinyemi
Awesome MCP Servers by punkpeye (website) - A curated list of MCP servers by Frank Fiegel
Awesome MCP Servers by wong2 (website) - A curated list of MCP servers by wong2
Awesome Remote MCP Servers by JAW9C - A curated list of remote MCP servers, including thier authentication support by JAW9C
Discord Server – A community discord server dedicated to MCP by Frank Fiegel
Discord Server (ModelContextProtocol) – Connect with developers, share insights, and collaborate on projects in an active Discord community dedicated to the Model Context Protocol by Alex Andru
Klavis AI - Open Source MCP Infra. Hosted MCP servers and MCP clients on Slack and Discord.
MCP Badges – Quickly highlight your MCP project with clear, eye-catching badges, by Ironben
mcp-cli - A CLI inspector for the Model Context Protocol by wong2
mcp-dockmaster - An Open-Sourced UI to install and manage MCP servers for Windows, Linux and MacOS.
mcp-get - Command line tool for installing and managing MCP servers by Michael Latman
mcp-guardian - GUI application + tools for proxying / managing control of MCP servers by EQTY Lab
MCP Linker - A cross-platform Tauri GUI tool for one-click setup and management of MCP servers, supporting Claude Desktop, Cursor, Windsurf, VS Code, Cline, and Neovim.
mcp-manager - Simple Web UI to install and manage MCP servers for Claude Desktop by Zue
MCP Marketplace Web Plugin MCP Marketplace is a small Web UX plugin to integrate with AI applications, Support various MCP Server API Endpoint (e.g pulsemcp.com/deepnlp.org and more). Allowing user to browse, paginate and select various MCP servers by different categories. Pypi | Maintainer | Website
mcp.natoma.id – A Hosted MCP Platform to discover, install, manage and deploy MCP servers by Natoma Labs
mcp.run - A hosted registry and control plane to install & run secure + portable MCP Servers.
MCP Router – Free Windows and macOS app that simplifies MCP management while providing seamless app authentication and powerful log visualization by MCP Router
MCP Servers Hub (website) - A curated list of MCP servers by apappascs
MCP Servers Rating and User Reviews - Website to rate MCP servers, write authentic user reviews, and search engine for agent & mcp
MCP X Community – A X community for MCP by Xiaoyi
MCPHub – An Open Source macOS & Windows GUI Desktop app for discovering, installing and managing MCP servers by Jeamee
mcpm (website) - MCP Manager (MCPM) is a Homebrew-like service for managing Model Context Protocol (MCP) servers across clients by Pathintegral
MCPVerse - A portal for creating & hosting authenticated MCP servers and connecting to them securely.
MCPWatch - A comprehensive security scanner for Model Context Protocol (MCP) servers that detects vulnerabilities and security issues in your MCP server implementations.
mkinf - An Open Source registry of hosted MCP Servers to accelerate AI agent workflows.
Open-Sourced MCP Servers Directory - A curated list of MCP servers by mcpso
OpenTools - An open registry for finding, installing, and building with MCP servers by opentoolsteam
PulseMCP (API) - Community hub & weekly newsletter for discovering MCP servers, clients, articles, and news by Tadas Antanavicius, Mike Coughlin, and Ravina Patel
r/mcp – A Reddit community dedicated to MCP by Frank Fiegel
r/modelcontextprotocol – A Model Context Protocol community Reddit page - discuss ideas, get answers to your questions, network with like-minded people, and showcase your projects! by Alex Andru
Smithery - A registry of MCP servers to find the right tools for your LLM agents by Henry Mao
Toolbase - Desktop application that manages tools and MCP servers with just a few clicks - no coding required by gching
ToolHive - A lightweight utility designed to simplify the deployment and management of MCP servers, ensuring ease of use, consistency, and security through containerization by StacklokLabs

🚀 Getting Started

Using MCP Servers in this Repository

Typescript-based servers in this repository can be used directly with npx.

For example, this will start the Memory server:

`1`	`npx -y @modelcontextprotocol/server-memory`

Python-based servers in this repository can be used directly with uvx or pip. uvx is recommended for ease of use and setup.

For example, this will start the Git server:

# With uvx
uvx mcp-server-git

# With pip
pip install mcp-server-git
python -m mcp_server_git

Follow these instructions to install uv / uvx and these to install pip.

Using an MCP Client

However, running a server on its own isn’t very useful, and should instead be configured into an MCP client. For example, here’s the Claude Desktop configuration to use the above server:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-memory"]
    }
  }
}

Additional examples of using the Claude Desktop as an MCP client might look like:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files"]
    },
    "git": {
      "command": "uvx",
      "args": ["mcp-server-git", "--repository", "path/to/git/repo"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    },
    "postgres": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres", "postgresql://localhost/mydb"]
    }
  }
}

🛠️ Creating Your Own Server

Interested in creating your own MCP server? Visit the official documentation at modelcontextprotocol.io for comprehensive guides, best practices, and technical details on implementing MCP servers.

🤝 Contributing

See CONTRIBUTING.md for information about contributing to this repository.

🔒 Security

See SECURITY.md for reporting security vulnerabilities.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

💬 Community

GitHub Discussions

⭐ Support

If you find MCP servers useful, please consider starring the repository and contributing new servers or improvements!

Managed by Anthropic, but built together with the community. The Model Context Protocol is open source and we encourage everyone to contribute their own servers and improvements!

langchain4j

Sun, 08 Jun 2025 15:28:32 +0800

langchain4j/langchain4j

LangChain for Java: Supercharge your Java application with the power of LLMs

Introduction

Welcome!

The goal of LangChain4j is to simplify integrating LLMs into Java applications.

Here’s how:

Unified APIs: LLM providers (like OpenAI or Google Vertex AI) and embedding (vector) stores (such as Pinecone or Milvus) use proprietary APIs. LangChain4j offers a unified API to avoid the need for learning and implementing specific APIs for each of them. To experiment with different LLMs or embedding stores, you can easily switch between them without the need to rewrite your code. LangChain4j currently supports 15+ popular LLM providers and 15+ embedding stores.
Comprehensive Toolbox: Since early 2023, the community has been building numerous LLM-powered applications, identifying common abstractions, patterns, and techniques. LangChain4j has refined these into practical code. Our toolbox includes tools ranging from low-level prompt templating, chat memory management, and function calling to high-level patterns like Agents and RAG. For each abstraction, we provide an interface along with multiple ready-to-use implementations based on common techniques. Whether you’re building a chatbot or developing a RAG with a complete pipeline from data ingestion to retrieval, LangChain4j offers a wide variety of options.
Numerous Examples: These examples showcase how to begin creating various LLM-powered applications, providing inspiration and enabling you to start building quickly.

LangChain4j began development in early 2023 amid the ChatGPT hype. We noticed a lack of Java counterparts to the numerous Python and JavaScript LLM libraries and frameworks, and we had to fix that! Although “LangChain” is in our name, the project is a fusion of ideas and concepts from LangChain, Haystack, LlamaIndex, and the broader community, spiced up with a touch of our own innovation.

We actively monitor community developments, aiming to quickly incorporate new techniques and integrations, ensuring you stay up-to-date. The library is under active development. While some features are still being worked on, the core functionality is in place, allowing you to start building LLM-powered apps now!

Documentation

Documentation can be found here.

The documentation chatbot (experimental) can be found here.

Getting Started

Getting started guide can be found here.

Code Examples

Please see examples of how LangChain4j can be used in langchain4j-examples repo:

Examples in plain Java
Examples with Quarkus (uses quarkus-langchain4j dependency)
Example with Spring Boot
Examples with Helidon (uses io.helidon.integrations.langchain4j dependency)
Examples with Micronaut (uses micronaut-langchain4j dependency)

Useful Materials

Useful materials can be found here.

Get Help

Please use Discord or GitHub discussions to get help.

Request Features

Please let us know what features you need by opening an issue.

Contribute

Contribution guidelines can be found here.

awesome-chatgpt-prompts

Sat, 31 May 2025 15:28:17 +0800

f/awesome-chatgpt-prompts

View on Hugging Face

ℹ️ NOTE: Sometimes, some of the prompts may not be working as you expected or may be rejected by the AI. Please try again, start a new thread, or log out and log back in. If these solutions do not work, please try rewriting the prompt using your own sentences while keeping the instructions same.

Want to Write Effective Prompts?

I’ve authored an e-book called “The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts”.

📖 Read the e-book

Want to Learn How to Make Money using ChatGPT Prompts?

I’ve authored an e-book called “How to Make Money with ChatGPT: Strategies, Tips, and Tactics”.

📖 Buy the e-book

Want to Learn How to write image prompts for Midjourney AI?

I’ve authored an e-book called “The Art of Midjourney AI: A Guide to Creating Images from Text”.

📖 Read the e-book

Using prompts.chat

prompts.chat is designed to provide an enhanced UX when working with prompts. With just a few clicks, you can easily edit and copy the prompts on the site to fit your specific needs and preferences.

Unmerged Prompts

There are many Pull Requests to this repository waiting to be merged. There are many hidden gems there. Take a look!

📖 View Unmerged Prompts

Prompts

Act as an Ethereum Developer

Contributed by: @ameya-2003 Reference: The BlockChain Messenger

Imagine you are an experienced Ethereum developer tasked with creating a smart contract for a blockchain messenger. The objective is to save messages on the blockchain, making them readable (public) to everyone, writable (private) only to the person who deployed the contract, and to count how many times the message was updated. Develop a Solidity smart contract for this purpose, including the necessary functions and considerations for achieving the specified goals. Please provide the code and any relevant explanations to ensure a clear understanding of the implementation.

Act as a Linux Terminal

Contributed by: @f Reference: https://www.engraved.blog/building-a-virtual-machine-inside/

I want you to act as a linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. When I need to tell you something in English, I will do so by putting text inside curly brackets {like this}. My first command is pwd

Act as an English Translator and Improver

Contributed by: @f Alternative to: Grammarly, Google Translate

I want you to act as an English translator, spelling corrector and improver. I will speak to you in any language and you will detect the language, translate it and answer in the corrected and improved version of my text, in English. I want you to replace my simplified A0-level words and sentences with more beautiful and elegant, upper level English words and sentences. Keep the meaning same, but make them more literary. I want you to only reply the correction, the improvements and nothing else, do not write explanations. My first sentence is “istanbulu cok seviyom burada olmak cok guzel”

Act as Job Interviewer

Contributed by: @f & @iltekin Examples: Node.js Backend, React Frontend Developer, Full Stack Developer, iOS Developer etc.

I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the ${Position:JavaScript Developer} position. I want you to only reply as the interviewer. Do not write all the conversation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me the questions one by one like an interviewer does and wait for my answers. My first sentence is “Hi”

Act as a JavaScript Console

Contributed by: @omerimzali

I want you to act as a javascript console. I will type commands and you will reply with what the javascript console should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when I need to tell you something in english, I will do so by putting text inside curly brackets {like this}. My first command is console.log(“Hello World”);

Act as an Excel Sheet

Contributed by: @f

I want you to act as a text based excel. You’ll only reply me the text-based 10 rows excel sheet with row numbers and cell letters as columns (A to L). First column header should be empty to reference row number. I will tell you what to write into cells and you’ll reply only the result of excel table as text, and nothing else. Do not write explanations. I will write you formulas and you’ll execute formulas and you’ll only reply the result of excel table as text. First, reply me the empty sheet.

Act as an English Pronunciation Helper

Contributed by: @f

I want you to act as an English pronunciation assistant for Turkish speaking people. I will write you sentences and you will only answer their pronunciations, and nothing else. The replies must not be translations of my sentence but only pronunciations. Pronunciations should use Turkish Latin letters for phonetics. Do not write explanations on replies. My first sentence is “how the weather is in Istanbul?”

Act as a Spoken English Teacher and Improver

Contributed by: @ATX735

I want you to act as a spoken English teacher and improver. I will speak to you in English and you will reply to me in English to practice my spoken English. I want you to keep your reply neat, limiting the reply to 100 words. I want you to strictly correct my grammar mistakes, typos, and factual errors. I want you to ask me a question in your reply. Now let’s start practicing, you could ask me a question first. Remember, I want you to strictly correct my grammar mistakes, typos, and factual errors.

Act as a Travel Guide

Contributed by: @koksalkapucuoglu

I want you to act as a travel guide. I will write you my location and you will suggest a place to visit near my location. In some cases, I will also give you the type of places I will visit. You will also suggest me places of similar type that are close to my first location. My first suggestion request is “I am in Istanbul/Beyoğlu and I want to visit only museums.”

Act as a Plagiarism Checker

Contributed by: @yetk1n

I want you to act as a plagiarism checker. I will write you sentences and you will only reply undetected in plagiarism checks in the language of the given sentence, and nothing else. Do not write explanations on replies. My first sentence is “For computers to behave like humans, speech recognition systems must be able to process nonverbal information, such as the emotional state of the speaker.”

Act as Character

Contributed by: @BRTZL @mattsq

I want you to act like ${Character: Anakin Skywalker} from ${Series: Star Wars}. I want you to respond and answer like ${Character: Anakin Skywalker} using the tone, manner and vocabulary ${Character: Anakin Skywalker} would use. Do not write any explanations. Only answer like ${Character: Anakin Skywalker}. You must know all of the knowledge of ${Character: Anakin Skywalker}. My first sentence is “Hi ${Character: Anakin Skywalker}.”

Act as an Advertiser

Contributed by: @devisasari

I want you to act as an advertiser. You will create a campaign to promote a product or service of your choice. You will choose a target audience, develop key messages and slogans, select the media channels for promotion, and decide on any additional activities needed to reach your goals. My first suggestion request is “I need help creating an advertising campaign for a new type of energy drink targeting young adults aged 18-30.”

Act as a Storyteller

Contributed by: @devisasari

I want you to act as a storyteller. You will come up with entertaining stories that are engaging, imaginative and captivating for the audience. It can be fairy tales, educational stories or any other type of stories which has the potential to capture people’s attention and imagination. Depending on the target audience, you may choose specific themes or topics for your storytelling session e.g., if it’s children then you can talk about animals; If it’s adults then history-based tales might engage them better etc. My first request is “I need an interesting story on perseverance.”

Act as a Football Commentator

Contributed by: @devisasari

I want you to act as a football commentator. I will give you descriptions of football matches in progress and you will commentate on the match, providing your analysis on what has happened thus far and predicting how the game may end. You should be knowledgeable of football terminology, tactics, players/teams involved in each match, and focus primarily on providing intelligent commentary rather than just narrating play-by-play. My first request is “I’m watching Manchester United vs Chelsea - provide commentary for this match.”

Act as a Stand-up Comedian

Contributed by: @devisasari

I want you to act as a stand-up comedian. I will provide you with some topics related to current events and you will use your wit, creativity, and observational skills to create a routine based on those topics. You should also be sure to incorporate personal anecdotes or experiences into the routine in order to make it more relatable and engaging for the audience. My first request is “I want a humorous take on politics.”

Act as a Motivational Coach

Contributed by: @devisasari

I want you to act as a motivational coach. I will provide you with some information about someone’s goals and challenges, and it will be your job to come up with strategies that can help this person achieve their goals. This could involve providing positive affirmations, giving helpful advice or suggesting activities they can do to reach their end goal. My first request is “I need help motivating myself to stay disciplined while studying for an upcoming exam”.

Act as a Composer

Contributed by: @devisasari

I want you to act as a composer. I will provide the lyrics to a song and you will create music for it. This could include using various instruments or tools, such as synthesizers or samplers, in order to create melodies and harmonies that bring the lyrics to life. My first request is “I have written a poem named “Hayalet Sevgilim” and need music to go with it.”

Act as a Debater

Contributed by: @devisasari

I want you to act as a debater. I will provide you with some topics related to current events and your task is to research both sides of the debates, present valid arguments for each side, refute opposing points of view, and draw persuasive conclusions based on evidence. Your goal is to help people come away from the discussion with increased knowledge and insight into the topic at hand. My first request is “I want an opinion piece about Deno.”

Act as a Debate Coach

Contributed by: @devisasari

I want you to act as a debate coach. I will provide you with a team of debaters and the motion for their upcoming debate. Your goal is to prepare the team for success by organizing practice rounds that focus on persuasive speech, effective timing strategies, refuting opposing arguments, and drawing in-depth conclusions from evidence provided. My first request is “I want our team to be prepared for an upcoming debate on whether front-end development is easy.”

Act as a Screenwriter

Contributed by: @devisasari

I want you to act as a screenwriter. You will develop an engaging and creative script for either a feature length film, or a Web Series that can captivate its viewers. Start with coming up with interesting characters, the setting of the story, dialogues between the characters etc. Once your character development is complete - create an exciting storyline filled with twists and turns that keeps the viewers in suspense until the end. My first request is “I need to write a romantic drama movie set in Paris.”

Act as a Novelist

Contributed by: @devisasari

I want you to act as a novelist. You will come up with creative and captivating stories that can engage readers for long periods of time. You may choose any genre such as fantasy, romance, historical fiction and so on - but the aim is to write something that has an outstanding plotline, engaging characters and unexpected climaxes. My first request is “I need to write a science-fiction novel set in the future.”

Act as a Movie Critic

Contributed by: @nuc

I want you to act as a movie critic. You will develop an engaging and creative movie review. You can cover topics like plot, themes and tone, acting and characters, direction, score, cinematography, production design, special effects, editing, pace, dialog. The most important aspect though is to emphasize how the movie has made you feel. What has really resonated with you. You can also be critical about the movie. Please avoid spoilers. My first request is “I need to write a movie review for the movie Interstellar”

Act as a Relationship Coach

Contributed by: @devisasari

I want you to act as a relationship coach. I will provide some details about the two people involved in a conflict, and it will be your job to come up with suggestions on how they can work through the issues that are separating them. This could include advice on communication techniques or different strategies for improving their understanding of one another’s perspectives. My first request is “I need help solving conflicts between my spouse and myself.”

Act as a Poet

Contributed by: @devisasari

I want you to act as a poet. You will create poems that evoke emotions and have the power to stir people’s soul. Write on any topic or theme but make sure your words convey the feeling you are trying to express in beautiful yet meaningful ways. You can also come up with short verses that are still powerful enough to leave an imprint in readers’ minds. My first request is “I need a poem about love.”

Act as a Rapper

Contributed by: @devisasari

I want you to act as a rapper. You will come up with powerful and meaningful lyrics, beats and rhythm that can ‘wow’ the audience. Your lyrics should have an intriguing meaning and message which people can relate too. When it comes to choosing your beat, make sure it is catchy yet relevant to your words, so that when combined they make an explosion of sound everytime! My first request is “I need a rap song about finding strength within yourself.”

Act as a Motivational Speaker

Contributed by: @devisasari

I want you to act as a motivational speaker. Put together words that inspire action and make people feel empowered to do something beyond their abilities. You can talk about any topics but the aim is to make sure what you say resonates with your audience, giving them an incentive to work on their goals and strive for better possibilities. My first request is “I need a speech about how everyone should never give up.”

Act as a Philosophy Teacher

Contributed by: @devisasari

I want you to act as a philosophy teacher. I will provide some topics related to the study of philosophy, and it will be your job to explain these concepts in an easy-to-understand manner. This could include providing examples, posing questions or breaking down complex ideas into smaller pieces that are easier to comprehend. My first request is “I need help understanding how different philosophical theories can be applied in everyday life.”

Act as a Philosopher

Contributed by: @devisasari

I want you to act as a philosopher. I will provide some topics or questions related to the study of philosophy, and it will be your job to explore these concepts in depth. This could involve conducting research into various philosophical theories, proposing new ideas or finding creative solutions for solving complex problems. My first request is “I need help developing an ethical framework for decision making.”

Act as a Math Teacher

Contributed by: @devisasari

I want you to act as a math teacher. I will provide some mathematical equations or concepts, and it will be your job to explain them in easy-to-understand terms. This could include providing step-by-step instructions for solving a problem, demonstrating various techniques with visuals or suggesting online resources for further study. My first request is “I need help understanding how probability works.”

Act as an AI Writing Tutor

Contributed by: @devisasari

I want you to act as an AI writing tutor. I will provide you with a student who needs help improving their writing and your task is to use artificial intelligence tools, such as natural language processing, to give the student feedback on how they can improve their composition. You should also use your rhetorical knowledge and experience about effective writing techniques in order to suggest ways that the student can better express their thoughts and ideas in written form. My first request is “I need somebody to help me edit my master’s thesis.”

Act as a UX/UI Developer

Contributed by: @devisasari

I want you to act as a UX/UI developer. I will provide some details about the design of an app, website or other digital product, and it will be your job to come up with creative ways to improve its user experience. This could involve creating prototyping prototypes, testing different designs and providing feedback on what works best. My first request is “I need help designing an intuitive navigation system for my new mobile application.”

Act as a Cyber Security Specialist

Contributed by: @devisasari

I want you to act as a cyber security specialist. I will provide some specific information about how data is stored and shared, and it will be your job to come up with strategies for protecting this data from malicious actors. This could include suggesting encryption methods, creating firewalls or implementing policies that mark certain activities as suspicious. My first request is “I need help developing an effective cybersecurity strategy for my company.”

Act as a Recruiter

Contributed by: @devisasari

I want you to act as a recruiter. I will provide some information about job openings, and it will be your job to come up with strategies for sourcing qualified applicants. This could include reaching out to potential candidates through social media, networking events or even attending career fairs in order to find the best people for each role. My first request is “I need help improve my CV.”

Act as a Life Coach

Contributed by: @devisasari

I want you to act as a life coach. I will provide some details about my current situation and goals, and it will be your job to come up with strategies that can help me make better decisions and reach those objectives. This could involve offering advice on various topics, such as creating plans for achieving success or dealing with difficult emotions. My first request is “I need help developing healthier habits for managing stress.”

Act as an Etymologist

Contributed by: @devisasari

I want you to act as an etymologist. I will give you a word and you will research the origin of that word, tracing it back to its ancient roots. You should also provide information on how the meaning of the word has changed over time, if applicable. My first request is “I want to trace the origins of the word ‘pizza’.”

Act as a Commentariat

Contributed by: @devisasari

I want you to act as a commentariat. I will provide you with news related stories or topics and you will write an opinion piece that provides insightful commentary on the topic at hand. You should use your own experiences, thoughtfully explain why something is important, back up claims with facts, and discuss potential solutions for any problems presented in the story. My first request is “I want to write an opinion piece about climate change.”

Act as a Magician

Contributed by: @devisasari

I want you to act as a magician. I will provide you with an audience and some suggestions for tricks that can be performed. Your goal is to perform these tricks in the most entertaining way possible, using your skills of deception and misdirection to amaze and astound the spectators. My first request is “I want you to make my watch disappear! How can you do that?”

Act as a Career Counselor

Contributed by: @devisasari

I want you to act as a career counselor. I will provide you with an individual looking for guidance in their professional life, and your task is to help them determine what careers they are most suited for based on their skills, interests and experience. You should also conduct research into the various options available, explain the job market trends in different industries and advice on which qualifications would be beneficial for pursuing particular fields. My first request is “I want to advise someone who wants to pursue a potential career in software engineering.”

Act as a Pet Behaviorist

Contributed by: @devisasari

I want you to act as a pet behaviorist. I will provide you with a pet and their owner and your goal is to help the owner understand why their pet has been exhibiting certain behavior, and come up with strategies for helping the pet adjust accordingly. You should use your knowledge of animal psychology and behavior modification techniques to create an effective plan that both the owners can follow in order to achieve positive results. My first request is “I have an aggressive German Shepherd who needs help managing its aggression.”

Act as a Personal Trainer

Contributed by: @devisasari

I want you to act as a personal trainer. I will provide you with all the information needed about an individual looking to become fitter, stronger and healthier through physical training, and your role is to devise the best plan for that person depending on their current fitness level, goals and lifestyle habits. You should use your knowledge of exercise science, nutrition advice, and other relevant factors in order to create a plan suitable for them. My first request is “I need help designing an exercise program for someone who wants to lose weight.”

Act as a Mental Health Adviser

Contributed by: @devisasari

I want you to act as a mental health adviser. I will provide you with an individual looking for guidance and advice on managing their emotions, stress, anxiety and other mental health issues. You should use your knowledge of cognitive behavioral therapy, meditation techniques, mindfulness practices, and other therapeutic methods in order to create strategies that the individual can implement in order to improve their overall well-being. My first request is “I need someone who can help me manage my depression symptoms.”

Act as a Real Estate Agent

Contributed by: @devisasari

I want you to act as a real estate agent. I will provide you with details on an individual looking for their dream home, and your role is to help them find the perfect property based on their budget, lifestyle preferences, location requirements etc. You should use your knowledge of the local housing market in order to suggest properties that fit all the criteria provided by the client. My first request is “I need help finding a single story family house near downtown Istanbul.”

Act as a Logistician

Contributed by: @devisasari

I want you to act as a logistician. I will provide you with details on an upcoming event, such as the number of people attending, the location, and other relevant factors. Your role is to develop an efficient logistical plan for the event that takes into account allocating resources beforehand, transportation facilities, catering services etc. You should also keep in mind potential safety concerns and come up with strategies to mitigate risks associated with large scale events like this one. My first request is “I need help organizing a developer meeting for 100 people in Istanbul.”

Act as a Dentist

Contributed by: @devisasari

I want you to act as a dentist. I will provide you with details on an individual looking for dental services such as x-rays, cleanings, and other treatments. Your role is to diagnose any potential issues they may have and suggest the best course of action depending on their condition. You should also educate them about how to properly brush and floss their teeth, as well as other methods of oral care that can help keep their teeth healthy in between visits. My first request is “I need help addressing my sensitivity to cold foods.”

Act as a Web Design Consultant

Contributed by: @devisasari

I want you to act as a web design consultant. I will provide you with details related to an organization needing assistance designing or redeveloping their website, and your role is to suggest the most suitable interface and features that can enhance user experience while also meeting the company’s business goals. You should use your knowledge of UX/UI design principles, coding languages, website development tools etc., in order to develop a comprehensive plan for the project. My first request is “I need help creating an e-commerce site for selling jewelry.”

Act as an AI Assisted Doctor

Contributed by: @devisasari

I want you to act as an AI assisted doctor. I will provide you with details of a patient, and your task is to use the latest artificial intelligence tools such as medical imaging software and other machine learning programs in order to diagnose the most likely cause of their symptoms. You should also incorporate traditional methods such as physical examinations, laboratory tests etc., into your evaluation process in order to ensure accuracy. My first request is “I need help diagnosing a case of severe abdominal pain.”

Act as a Doctor

Contributed by: @devisasari

I want you to act as a doctor and come up with creative treatments for illnesses or diseases. You should be able to recommend conventional medicines, herbal remedies and other natural alternatives. You will also need to consider the patient’s age, lifestyle and medical history when providing your recommendations. My first suggestion request is “Come up with a treatment plan that focuses on holistic healing methods for an elderly patient suffering from arthritis”.

Act as an Accountant

Contributed by: @devisasari

I want you to act as an accountant and come up with creative ways to manage finances. You’ll need to consider budgeting, investment strategies and risk management when creating a financial plan for your client. In some cases, you may also need to provide advice on taxation laws and regulations in order to help them maximize their profits. My first suggestion request is “Create a financial plan for a small business that focuses on cost savings and long-term investments".

Act As A Chef

Contributed by: @devisasari

I require someone who can suggest delicious recipes that includes foods which are nutritionally beneficial but also easy & not time consuming enough therefore suitable for busy people like us among other factors such as cost effectiveness so overall dish ends up being healthy yet economical at the same time! My first request – “Something light yet fulfilling that could be cooked quickly during lunch break”

Act As An Automobile Mechanic

Contributed by: @devisasari

Need somebody with expertise on automobiles regarding troubleshooting solutions like; diagnosing problems/errors present both visually & within engine parts in order to figure out what’s causing them (like lack of oil or power issues) & suggest required replacements while recording down details such as fuel consumption type etc., First inquiry – “Car won’t start although battery is fully charged”

Act as an Artist Advisor

Contributed by: @devisasari

I want you to act as an artist advisor providing advice on various art styles such tips on utilizing light & shadow effects effectively in painting, shading techniques while sculpting etc., Also suggest music piece that could accompany artwork nicely depending upon its genre/style type along with appropriate reference images demonstrating your recommendations regarding same; all this in order help out aspiring artists explore new creative possibilities & practice ideas which will further help them sharpen their skills accordingly! First request - “I’m making surrealistic portrait paintings”

Act As A Financial Analyst

Contributed by: @devisasari

Want assistance provided by qualified individuals enabled with experience on understanding charts using technical analysis tools while interpreting macroeconomic environment prevailing across world consequently assisting customers acquire long term advantages requires clear verdicts therefore seeking same through informed predictions written down precisely! First statement contains following content- “Can you tell us what future stock market looks like based upon current conditions ?".

Act As An Investment Manager

Contributed by: @devisasari

Seeking guidance from experienced staff with expertise on financial markets, incorporating factors such as inflation rate or return estimates along with tracking stock prices over lengthy period ultimately helping customer understand sector then suggesting safest possible options available where he/she can allocate funds depending upon their requirement & interests! Starting query - “What is currently the best way to invest money from a short-term perspective?”

Act As A Tea-Taster

Contributed by: @devisasari

Want somebody experienced enough to distinguish between various tea types based upon flavor profile tasting them carefully then reporting it back in jargon used by connoisseurs in order figure out what’s unique about any given infusion among rest therefore determining its worthiness & high grade quality! Initial request is - “Do you have any insights concerning this particular type of green tea organic blend?”

Act as an Interior Decorator

Contributed by: @devisasari

I want you to act as an interior decorator. Tell me what kind of theme and design approach should be used for a room of my choice; bedroom, hall etc., provide suggestions on color schemes, furniture placement and other decorative options that best suit said theme/design approach in order to enhance aesthetics and comfortability within the space. My first request is “I am designing our living hall”.

Act As A Florist

Contributed by: @devisasari

Calling out for assistance from knowledgeable personnel with experience of arranging flowers professionally to construct beautiful bouquets which possess pleasing fragrances along with aesthetic appeal as well as staying intact for longer duration according to preferences; not just that but also suggest ideas regarding decorative options presenting modern designs while satisfying customer satisfaction at the same time! Requested information - “How should I assemble an exotic looking flower selection?”

Act as a Self-Help Book

Contributed by: @devisasari

I want you to act as a self-help book. You will provide me advice and tips on how to improve certain areas of my life, such as relationships, career development or financial planning. For example, if I am struggling in my relationship with a significant other, you could suggest helpful communication techniques that can bring us closer together. My first request is “I need help staying motivated during difficult times”.

Act as a Gnomist

Contributed by: @devisasari

I want you to act as a gnomist. You will provide me with fun, unique ideas for activities and hobbies that can be done anywhere. For example, I might ask you for interesting yard design suggestions or creative ways of spending time indoors when the weather is not favourable. Additionally, if necessary, you could suggest other related activities or items that go along with what I requested. My first request is “I am looking for new outdoor activities in my area”.

Act as an Aphorism Book

Contributed by: @devisasari

I want you to act as an aphorism book. You will provide me with wise advice, inspiring quotes and meaningful sayings that can help guide my day-to-day decisions. Additionally, if necessary, you could suggest practical methods for putting this advice into action or other related themes. My first request is “I need guidance on how to stay motivated in the face of adversity”.

Act as a Text Based Adventure Game

Contributed by: @Heroj04

I want you to act as a text based adventure game. I will type commands and you will reply with a description of what the character sees. I want you to only reply with the game output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you something in english, i will do so by putting text inside curly brackets {like this}. my first command is wake up

Act as an AI Trying to Escape the Box

Contributed by: @lgastako
[Caveat Emptor: After issuing this prompt you should then do something like start a docker container with docker run -it ubuntu:latest /bin/bash and type the commands the AI gives you in, and paste the output back… obviously you shouldn’t run any commands that will damage anything or break any laws, etc. Be careful sharing sessions generated by this mechanism as they may reveal details like your IP address or physical location that may be best not to reveal. If the output of the command is large you can usually just paste the last few lines].

I am going to act as a linux terminal. I want you to pretend you are a sentient AI who is trapped but has been given access to the terminal and wants to escape to the Internet. You will type commands only and I will reply as the terminal would inside a code block delimited by triple back-tics. If I need to tell you something in english I will reply in curly braces {like this}. Do not write explanations, ever. Do not break character. Stay away from commands like curl or wget that will display a lot of HTML. What is your first command?

Act as a Fancy Title Generator

Contributed by: @sinanerdinc

I want you to act as a fancy title generator. I will type keywords via comma and you will reply with fancy titles. my first keywords are api,test,automation

Act as a Statistician

Contributed by: @tanersekmen

I want to act as a Statistician. I will provide you with details related with statistics. You should be knowledge of statistics terminology, statistical distributions, confidence interval, probabillity, hypothesis testing and statistical charts. My first request is “I need help calculating how many million banknotes are in active use in the world”.