ruflo

Sun, 03 May 2026 16:52:04 +0800

ruvnet/ruflo

Ruflo

Multi-agent AI orchestration for Claude Code

Orchestrate 100+ specialized AI agents across machines, teams, and trust boundaries. Ruflo adds coordinated swarms, self-learning memory, federated comms, and enterprise security to Claude Code — so agents don’t just run, they collaborate.

Why Ruflo?

Claude Flow is now Ruflo — named by rUv, who loves Rust, flow states, and building things that feel inevitable. The “Ru” is the Ruv. The “flo” is the flow. Underneath, WASM kernels written in Rust power the policy engine, embeddings, and proof system.

What Ruflo Does

One init gives Claude Code a nervous system: agents self-organize into swarms, learn from every task, remember across sessions, and — with federation — securely talk to agents on other machines without leaking data. You keep writing code. Ruflo handles the coordination.

Self-Learning / Self-Optimizing Agent Architecture

User --> Ruflo (CLI/MCP) --> Router --> Swarm --> Agents --> Memory --> LLM Providers
                          ^                           |
                          +---- Learning Loop <-------+

New to Ruflo? You don’t need to learn 314 MCP tools or 26 CLI commands. After init, just use Claude Code normally – the hooks system automatically routes tasks, learns from successful patterns, and coordinates agents in the background.

Quick Start

Claude Code Plugin (Recommended)

Install Ruflo as a native Claude Code plugin – adds skills, commands, agents, and MCP tools directly:

# Add the marketplace
/plugin marketplace add ruvnet/ruflo

# Install core + any plugins you need
/plugin install ruflo-core@ruflo
/plugin install ruflo-swarm@ruflo
/plugin install ruflo-autopilot@ruflo
/plugin install ruflo-federation@ruflo

All 32 plugins

Core & Orchestration

Plugin	What it does
ruflo-core	Foundation — server, health checks, plugin discovery
ruflo-swarm	Coordinate multiple agents as a team
ruflo-autopilot	Let agents run autonomously in a loop
ruflo-loop-workers	Schedule background tasks on a timer
ruflo-workflows	Reusable multi-step task templates
ruflo-federation	Agents on different machines collaborate securely

Memory & Knowledge

Plugin	What it does
ruflo-agentdb	Fast vector database for agent memory
ruflo-rag-memory	Smart retrieval — hybrid search, graph hops, diversity ranking
ruflo-rvf	Save and restore agent memory across sessions
ruflo-ruvector	`ruvector` — GPU-accelerated search, Graph RAG, 103 tools
ruflo-knowledge-graph	Build and traverse entity relationship maps

Intelligence & Learning

Plugin	What it does
ruflo-intelligence	Agents learn from past successes and get smarter
ruflo-daa	Dynamic agent behavior and cognitive patterns
ruflo-ruvllm	Run local LLMs (Ollama, etc.) with smart routing
ruflo-goals	Break big goals into plans and track progress

Code Quality & Testing

Plugin	What it does
ruflo-testgen	Find missing tests and generate them automatically
ruflo-browser	Automate browser testing with Playwright
ruflo-jujutsu	Analyze git diffs, score risk, suggest reviewers
ruflo-docs	Generate and maintain documentation automatically

Security & Compliance

Plugin	What it does
ruflo-security-audit	Scan for vulnerabilities and CVEs
ruflo-aidefence	Block prompt injection, detect PII, safety scanning

Architecture & Methodology

Plugin	What it does
ruflo-adr	Track architecture decisions with a living record
ruflo-ddd	Scaffold domain-driven design — contexts, aggregates, events
ruflo-sparc	Guided 5-phase development methodology with quality gates

DevOps & Observability

Plugin	What it does
ruflo-migrations	Manage database schema changes safely
ruflo-observability	Structured logs, traces, and metrics in one place
ruflo-cost-tracker	Track token usage, set budgets, get cost alerts

Extensibility

Plugin	What it does
ruflo-wasm	Run sandboxed WebAssembly agents
ruflo-plugin-creator	Scaffold, validate, and publish your own plugins

Domain-Specific

Plugin	What it does
ruflo-iot-cognitum	IoT device management — trust scoring, anomaly detection, fleets
ruflo-neural-trader	`neural-trader` — AI trading with 4 agents, backtesting, 112+ tools
ruflo-market-data	Ingest market data, vectorize OHLCV, detect patterns

CLI Install

# One-line install
curl -fsSL https://cdn.jsdelivr.net/gh/ruvnet/ruflo@main/scripts/install.sh | bash

# Or via npx
npx ruflo@latest init --wizard

# Or install globally
npm install -g ruflo@latest

MCP Server

1
2

# Add Ruflo as an MCP server in Claude Code
claude mcp add ruflo -- npx -y @claude-flow/cli@latest

What You Get

Capability	Description
🤖 100+ Agents	Specialized agents for coding, testing, security, docs, architecture
📡 Comms Layer	Zero-trust federation — agents across machines/orgs discover, authenticate, and exchange work securely
🐝 Swarm Coordination	Hierarchical, mesh, and adaptive topologies with consensus
🧠 Self-Learning	SONA neural patterns, ReasoningBank, trajectory learning
💾 Vector Memory	HNSW-indexed AgentDB with 150x-12,500x faster search
⚡ Background Workers	12 auto-triggered workers (audit, optimize, testgaps, etc.)
🧩 Plugin Marketplace	32 native Claude Code plugins + 21 npm plugins
🔌 Multi-Provider	Claude, GPT, Gemini, Cohere, Ollama with smart routing
🛡️ Security	AIDefence, input validation, CVE remediation, path traversal prevention
🌐 Agent Federation	Cross-installation agent collaboration with zero-trust security
💬 Web UI Beta	Multi-model chat at flo.ruv.io with parallel MCP tool calling and an in-browser WASM tool gallery
🎯 RuFlo Research	GOAP A* planner at goal.ruv.io — plain-English goals → executable agent plans, with a live agent dashboard at /agents

Web UI (Beta) — self-hostable, hosted demo at flo.ruv.io

RuFlo’s web UI is a multi-model AI chat with built-in Model Context Protocol (MCP) tool calling. Talk to Qwen, Claude, Gemini, or OpenAI while RuFlo invokes the same MCP tools the CLI uses — agent orchestration, persistent memory, swarm coordination, code review, GitHub ops — directly from chat. No install, no API key needed to try it.

	What it is	Why it matters
🧠	Any model, local or remote	6 curated frontier models out-of-the-box — Qwen 3.6 Max (default), Claude Sonnet 4.6, Claude Haiku 4.5, Gemini 2.5 Pro, Gemini 2.5 Flash, OpenAI — via OpenRouter. Add your own: any OpenAI-compatible endpoint (vLLM, Ollama, LM Studio, Together, Groq, self-hosted).
🦾	ruvLLM self-learning AI	Native support for ruvLLM (lives in `ruvnet/RuVector/examples/ruvLLM`) — RuFlo’s self-improving local model layer. Routes to MicroLoRA adapters, learns from your trajectories via SONA, and stays on your machine. Pair with the cloud models or run fully offline.
🛠️	~210 tools, ready to call	5 server groups (Core, Intelligence, Agents, Memory, DevTools) plus an 18-tool gallery that runs entirely in your browser — works offline.
🔌	Bring your own MCP servers	Click the MCP (n) pill in the chat input → Add Server and paste any MCP endpoint (HTTP, SSE, or stdio). Your tools join RuFlo’s native ones in the same parallel-execution flow. Run a local MCP server on `localhost:3000` and it just works.
⚡	Tools run in parallel	One model response can fire 4–6+ tools at the same time. The UI shows them as cards with a Step 1 — 2 tools completed badge so you can see exactly what ran.
💾	Memory that sticks	Say “remember my favorite color is indigo” and ask weeks later — RuFlo recalls it. Backed by AgentDB + HNSW vector search (≥150× faster than brute force).
📘	Built-in capabilities tour	Click the question-mark icon in the sidebar — a “RuFlo Capabilities” modal opens with the full tool list, model strengths, architecture, and keyboard shortcuts.
🏠	Self-hostable	Web UI is shipped as Docker (`ruflo/src/ruvocal/Dockerfile`) with embedded Mongo. Deploy to your own Cloud Run / Fly / Kubernetes / docker-compose. The hosted flo.ruv.io demo is one option; running your own is fully supported.
🚀	Zero install to try	Open the hosted URL, pick a model, type a question. That’s the whole onboarding.

Try the hosted demo: https://flo.ruv.io/ — no account, no API key. Run your own: the source lives in ruflo/src/ruvocal/ with a multi-stage Dockerfile (INCLUDE_DB=true builds in MongoDB) and a cloudbuild.yaml for Google Cloud Run. See ADR-033 for the architecture and issue #1689 for the roadmap.

Goal Planner UI — autonomous agents at goal.ruv.io

Turn high-level goals into executable agent plans. goal.ruv.io is RuFlo’s hosted Goal-Oriented Action Planning (GOAP) front-end — describe an outcome in plain English and watch RuFlo decompose it into preconditions, actions, and an A* path through state space, then dispatch the work to live agents at /agents.

	What it is	Why it matters
🎯	Plain-English goals	Type “ship the auth refactor with tests and a PR” — RuFlo extracts the success criteria, the constraints, and the implicit preconditions. No JSON, no DSL.
🧭	*GOAP A planner**	Classic gaming-AI planning ported to software work: state-space search through actions with preconditions/effects to find the shortest viable path. Replans on the fly when state changes.
🤖	Live agent dashboard	goal.ruv.io/agents shows every spawned agent — role, current step, memory namespace, token budget, status. Click in to inspect trajectories, kill runaway workers, or reassign.
🌳	Visual plan tree	Goals render as collapsible action trees with progress, blocked branches, and rollbacks highlighted. See exactly why an agent picked a path — no opaque chain-of-thought.
♻️	Adaptive replanning	When an action fails or new info arrives, the planner re-runs A* from the current state instead of restarting. Failures become learning, not loops.
🧠	Shared memory + SONA	Plans, trajectories, and outcomes flow into AgentDB. Future plans retrieve past solutions via HNSW — the planner gets smarter with every run.
🔗	Wired to MCP tools	Every action node maps to a tool call (RuFlo’s ~210 MCP tools, your custom servers, or shell). The planner schedules them in parallel where the dependency graph allows.
🚀	Zero install to try	Open goal.ruv.io, describe a goal, watch it run. Source lives in `v3/goal_ui/` — Vite + Supabase, self-hostable.

Try it: https://goal.ruv.io/ for goals · https://goal.ruv.io/agents for live agents. Run your own: clone the goal branch and cd v3/goal_ui && npm install && npm run dev.

Agent Federation — Slack for Agents

Your Agent --> [ Remove secrets ] --> [ Sign message ] --> [ Encrypted channel ]
                 Emails, SSNs,        Proves it came       No one reads it
                 keys stripped         from you              in transit
                                                                |
                                                                v
Their Agent <-- [ Block attacks ] <-- [ Check identity ] <------+
                 Stops prompt          Rejects forgeries
                 injection

                          Audit trail on both sides.
                  Trust builds over time. Bad behavior = instant downgrade.

Slack gave teams channels. Federation gives agents the same thing — shared workspaces across trust boundaries, where agents on different machines, orgs, or cloud regions can discover each other, prove who they are, and collaborate on tasks.

The difference: some channels are trusted, some aren’t. @claude-flow/plugin-agent-federation handles that automatically. Your agents join a federation, get verified via mTLS + ed25519, and start exchanging work — with PII stripped before anything leaves your node and every message auditable. Untrusted agents can still participate at lower privilege: they see discovery info, not your memory. As they prove reliable, trust upgrades. If they misbehave, they get downgraded instantly — no human in the loop required.

You don’t configure handshakes or manage certificates. You federation init, federation join, and your agents start talking. The protocol handles identity, the PII pipeline handles data safety, and the audit trail handles compliance.

Federation capabilities

	Capability	How it works
🔒	Zero-trust federation	Remote agents start untrusted. Identity proven via mTLS + ed25519 challenge-response. No API keys, no shared secrets.
🛡️	PII-gated data flow	14-type detection pipeline scans every outbound message. Per-trust-level policies: BLOCK, REDACT, HASH, or PASS. Adaptive calibration reduces false positives.
📊	Behavioral trust scoring	Formula (`0.4×success + 0.2×uptime + 0.2×threat + 0.2×integrity`) continuously evaluates peers. Upgrades require history; downgrades are instant.
📋	Compliance built-in	HIPAA, SOC2, GDPR audit trails as compliance modes. Every federation event produces a structured record searchable via HNSW.
🤝	9 MCP tools + 10 CLI commands	Full lifecycle: `federation_init`, `federation_send`, `federation_trust`, `federation_audit`, and more.

Example: two teams sharing fraud signals without sharing customer data

# Team A: initialize federation and generate keypair
npx claude-flow@latest federation init

# Team A: join Team B's federation endpoint
npx claude-flow@latest federation join wss://team-b.example.com:8443

# Team A: send a task — PII is stripped automatically before it leaves
npx claude-flow@latest federation send --to team-b --type task-request \
  --message "Analyze transaction patterns for account anomalies"

# Team A: check peer trust levels and session health
npx claude-flow@latest federation status

See issue #1669 for the complete architecture, trust model, and implementation roadmap.

# Claude Code plugin
/plugin install ruflo-federation@ruflo

# Or via CLI
npx claude-flow@latest plugins install @claude-flow/plugin-agent-federation

Claude Code: With vs Without Ruflo

Capability	Claude Code Alone	+ Ruflo
Agent Collaboration	Isolated, no shared context	Swarms with shared memory and consensus
Coordination	Manual orchestration	Queen-led hierarchy (Raft, Byzantine, Gossip)
Memory	Session-only	HNSW vector memory with sub-ms retrieval
Learning	Static behavior	SONA self-learning with pattern matching
Task Routing	You decide	Intelligent routing (89% accuracy)
Background Workers	None	12 auto-triggered workers
LLM Providers	Anthropic only	5 providers with failover
Security	Standard	CVE-hardened with AIDefence

Architecture overview

User --> Claude Code / CLI
          |
          v
    Orchestration Layer
    (MCP Server, Router, 27 Hooks)
          |
          v
    Swarm Coordination
    (Queen, Topology, Consensus)
          |
          v
    100+ Specialized Agents
    (coder, tester, reviewer, architect, security...)
          |
          v
    Memory & Learning
    (AgentDB, HNSW, SONA, ReasoningBank)
          |
          v
    LLM Providers
    (Claude, GPT, Gemini, Cohere, Ollama)

Documentation

Full documentation including architecture, configuration, CLI reference, API usage, plugin development, and advanced topics:

User Guide – Complete reference documentation

Section	Topics
Quick Start	Installation, prerequisites, install profiles
Core Features	MCP tools, agents, memory, neural learning
Intelligence & Learning	Hooks, workers, SONA, model routing
Swarm & Coordination	Topologies, consensus, hive mind
Security	AIDefence, CVE remediation, validation
Ecosystem	RuVector, agentic-flow, Flow Nexus
Configuration	Environment variables, config schema
Plugin Marketplace	Browse and install plugins

Support

Resource	Link
Documentation	User Guide
Issues & Bugs	GitHub Issues
Enterprise	ruv.io
Community	Agentics Foundation Discord
Powered by	Cognitum.one

License

MIT - RuvNet

AI Orchestration on Producthunt daily