Ruflo

[](https://cognitum.one/agentic-engineering)

[](https://flo.ruv.io/) [](https://www.npmjs.com/package/ruflo) [](https://opensource.org/licenses/MIT) [](https://github.com/ruvnet/claude-flow)

[](https://goal.ruv.io/) [](https://goal.ruv.io/agents) [](https://github.com/ruvnet/ruvector) [](https://github.com/ruvnet/ruflo/blob/main/data/clone-data.proof.json) [](https://github.com/ruvnet/ruflo/blob/main/data/clone-data.ledger.json) [](https://github.com/ruvnet/claude-flow) [](https://www.npmjs.com/package/@claude-flow/codex)

Ruflo

An agent meta-harness for Claude Code and Codex.

> 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.

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`](https://ruv.io), 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`](https://cognitum.one/?RuFlo) agentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.

---

## 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 | **No** (`memory_store`, `swarm_init`, etc. unavailable to Claude) | 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 only. The Ruflo MCP server is NOT registered, so memory_store, swarm_init, agent_spawn, etc. won't be callable from Claude. For the full loop, use Path B below.

🔌 All 35 plugins

Core & Orchestration

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

Memory & Knowledge

| Plugin | What it does | |--------|-------------| | [ruflo-agentdb](plugins/ruflo-agentdb/README.md) | Fast vector database for agent memory | | [ruflo-rag-memory](plugins/ruflo-rag-memory/README.md) | Smart retrieval — hybrid search, graph hops, diversity ranking | | [ruflo-rvf](plugins/ruflo-rvf/README.md) | Save and restore agent memory across sessions | | [ruflo-ruvector](plugins/ruflo-ruvector/README.md) | ruvector — GPU-accelerated search, Graph RAG, 103 tools | | [ruflo-knowledge-graph](plugins/ruflo-knowledge-graph/README.md) | Build and traverse entity relationship maps |

Intelligence & Learning

| Plugin | What it does | |--------|-------------| | [ruflo-intelligence](plugins/ruflo-intelligence/README.md) | Agents learn from past successes and get smarter | | [ruflo-graph-intelligence](plugins/ruflo-graph-intelligence/) | Sublinear graph reasoning — PageRank, delta updates, complexity-aware execution (ADR-123) | | [ruflo-daa](plugins/ruflo-daa/README.md) | Dynamic agent behavior and cognitive patterns | | [ruflo-ruvllm](plugins/ruflo-ruvllm/README.md) | Run local LLMs (Ollama, etc.) with smart routing | | [ruflo-goals](plugins/ruflo-goals/README.md) | Break big goals into plans and track progress |

Code Quality & Testing

| Plugin | What it does | |--------|-------------| | [ruflo-testgen](plugins/ruflo-testgen/README.md) | Find missing tests and generate them automatically | | [ruflo-browser](plugins/ruflo-browser/README.md) | Automate browser testing with Playwright | | [ruflo-jujutsu](plugins/ruflo-jujutsu/README.md) | Analyze git diffs, score risk, suggest reviewers | | [ruflo-docs](plugins/ruflo-docs/README.md) | Generate and maintain documentation automatically |

Security & Compliance

| Plugin | What it does | |--------|-------------| | [ruflo-security-audit](plugins/ruflo-security-audit/README.md) | Scan for vulnerabilities and CVEs | | [ruflo-aidefence](plugins/ruflo-aidefence/README.md) | Block prompt injection, detect PII, safety scanning |

Architecture & Methodology

| Plugin | What it does | |--------|-------------| | [ruflo-adr](plugins/ruflo-adr/README.md) | Track architecture decisions with a living record | | [ruflo-ddd](plugins/ruflo-ddd/README.md) | Scaffold domain-driven design — contexts, aggregates, events | | [ruflo-sparc](plugins/ruflo-sparc/README.md) | Guided 5-phase development methodology with quality gates | | [ruflo-metaharness](plugins/ruflo-metaharness/README.md) | Grade your agent setup, scan tool configs for security risks, and track changes over time ([guide](docs/metaharness-user-guide.md)) | | [ruflo-arena](plugins/ruflo-arena/README.md) | 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](plugins/ruflo-migrations/README.md) | Manage database schema changes safely | | [ruflo-observability](plugins/ruflo-observability/README.md) | Structured logs, traces, and metrics in one place | | [ruflo-cost-tracker](plugins/ruflo-cost-tracker/README.md) | Track token usage, set budgets, get cost alerts |

Extensibility

| Plugin | What it does | |--------|-------------| | [ruflo-agent](plugins/ruflo-agent/README.md) | Run agents — local WASM sandbox (rvagent) + Anthropic Claude Managed Agents (cloud) | | [ruflo-plugin-creator](plugins/ruflo-plugin-creator/README.md) | Scaffold, validate, and publish your own plugins |

Domain-Specific

| Plugin | What it does | |--------|-------------| | [ruflo-iot-cognitum](plugins/ruflo-iot-cognitum/README.md) | IoT device management — trust scoring, anomaly detection, fleets | | [ruflo-neural-trader](plugins/ruflo-neural-trader/README.md) | neural-trader — AI trading with 4 agents, backtesting, 112+ tools | | [ruflo-market-data](plugins/ruflo-market-data/README.md) | Ingest market data, vectorize OHLCV, detect patterns |

CLI Install

macOS / Linux / WSL / Git-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):

# 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

# Add Ruflo as an MCP server in Claude Code (canonical form, matches USERGUIDE.md)
claude mcp add ruflo -- 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](docs/reviews/intelligence-system-audit-2026-05-29.md) + [scripts/benchmark-intelligence.mjs](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](docs/metaharness-user-guide.md) | 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](docs/metaharness-user-guide.md). | | 💬 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/](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](ruflo/docs/adr/ADR-033-RUVOCAL-WASM-MCP-INTEGRATION.md) 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 beco

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ruvnet
• Source: ruvnet/ruflo
• License: MIT
• Homepage: https://Cognitum.One

Install and usage instructions live in the source repository linked above.