Ruflo

An agent meta-harness for Claude Code and Codex.

📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification.

Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work. Ruflo is the harness — the execution layer around Claude Code and Codex that adds 100+ specialized agents, coordinated swarms, self-learning memory, federated comms across machines, and enterprise security guardrails. So agents don't just run, they collaborate.

One npx ruflo 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.

Code

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.

📖 Background — where the name comes from

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 working until 3am. Underneath, powered by Cognitum.One agentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.

Ruflo Plugins

Quick Start

There are two different install paths with very different surface areas. Pick based on what you need (#1744):

	Claude Code Plugin	CLI install (`npx ruflo init`)
What it gives you	Slash commands + a few skills + agent definitions per-plugin	Full Ruflo loop — 98 agents, 60+ commands, 30 skills, MCP server, hooks, daemon
Files in your workspace	Zero	`.claude/`, `.claude-flow/`, `CLAUDE.md`, helpers, settings
MCP server registered	Only if `ruflo-core` is installed (it ships its own `.mcp.json`) — most other plugins don't	Yes
Hooks installed	No	Yes
Best for	Try a single plugin's commands without committing to the full install	Production use — everything works as documented

Path A — Claude Code Plugins (lite, slash commands only)

bash

# 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-rag-memory@ruflo
/plugin install ruflo-neural-trader@ruflo

This adds slash commands and agent definitions. ruflo-core (installed above) does register its own MCP server on install — its tools are callable as mcp__plugin_ruflo-core_ruflo__* (e.g. mcp__plugin_ruflo-core_ruflo__memory_store), not the bare memory_store/swarm_init/agent_spawn names the CLI-track scaffold uses. Other plugins generally don't ship their own MCP server. For the full loop with the CLI-track tool names, use Path B below.

🔌 All 35 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-graph-intelligence	Sublinear graph reasoning — PageRank, delta updates, complexity-aware execution (ADR-123)
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
ruflo-metaharness	Grade your agent setup, scan tool configs for security risks, and track changes over time (guide)
ruflo-arena	Competitive ruliology — pit agent strategies against each other in tournaments, hill-climb and co-evolve the winners (ADR-147/148)

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-agent	Run agents — local WASM sandbox (rvagent) + Anthropic Claude Managed Agents (cloud)
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

macOS / Linux / WSL / Git-Bash:

bash

# One-line install (POSIX shells only — see Windows note below)
curl -fsSL https://cdn.jsdelivr.net/gh/ruvnet/ruflo@main/scripts/install.sh | bash

All platforms (including native Windows PowerShell / cmd):

bash

# Interactive setup wizard — runs identically on every platform
npx ruflo@latest init wizard

# Quick non-interactive init
# npx ruflo@latest init

# Or install globally
npm install -g ruflo@latest

💡 Windows users: the curl ... | bash form needs a POSIX shell (Git-Bash, WSL, MSYS). The npx ruflo@latest init wizard line works natively in PowerShell and cmd. If you hit an 'bash' is not recognized error, use the npx line instead — both end up running the same init flow.

MCP Server

bash

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

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 — measured ~1.9x faster at N=20k, ~3.2x–4.7x at N=5k vs brute force (recall@10 ~0.99); ANN wins above the crossover, ties/loses at small N. See audit + `scripts/benchmark-intelligence.mjs`
⚡ Background Workers	12 auto-triggered workers (audit, optimize, testgaps, etc.)
🧩 Plugin Marketplace	33 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
🔬 MetaHarness	Audit your AI agent setup before you ship. Grade readiness (1-100), scan tool configs for security issues, snapshot the whole project to catch regressions over time, and find templates that match your repo. `ruflo eject` turns a ruflo project into a standalone agent toolkit with its own name. Full guide.
💬 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 (measured ~1.9x–4.7x faster than brute force above the crossover, recall@10 ~0.99).
📘	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

Code

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.

📘 Full user guide: docs/federation/ — setup, MCP tools, trust levels, circuit breaker, and the (opt-in) WireGuard mesh layer that ties packet-layer reachability to federation trust. ADR-111 deep-dive at docs/federation/phase7-mesh-bringup.md.

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

bash

# 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.

bash

# 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

Code

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

Four docs for four audiences:

Doc	When to read it
Status	See what currently works — capability counts, test baselines, recent fixes, what's next. The is-it-ready doc.
User Guide	Daily reference — every command, every config flag, every plugin. The how-do-I doc.
MetaHarness Guide	How to grade your agent setup, scan tool configs for security, detect changes between runs, and eject a project into a standalone agent toolkit. The audit-my-setup doc.
Benchmarks	v3.8.0 SOTA matrix vs LangGraph / AutoGen / CrewAI on darwin-arm64 + linux-x64. ruflo wins cold start, single turn, RSS by 1.3×–1953×. The is-it-fast doc.
Verification	Cryptographically prove your installed bytes match the signed witness — `ruflo verify`. The trust-but-verify doc.
Team Gateway Checklist	Before-merge gates, dual-mode handoff, memory namespace sharing, and witness manifest entry per merge. The safer-team-workflows doc.

Benchmark internals (for reproduction): sota-workload-spec.md · SOTA-PROGRESS.md · raw matrix JSON: darwin · linux

User Guide section index:

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