Get started with Ruflo

Start in Claude Code with core tools, the visual console and runtime mods. Requires Claude Code 2.1.287 or later. Run inside Claude Code:

/plugin marketplace add ruvnet/ruflo
/plugin install ruflo-core@ruflo
/plugin install ruflo-console@ruflo
/plugin install ruflo-mods@ruflo
/reload-plugins
/ruflo

Core provides foundation tools. Console opens the agent cockpit. Mods add routing and policy enforcement inside Claude Code. Mods run with your account's permissions; review their code before installing.

Using Codex or another MCP enabled tool? Use NPX for Ruflo project setup and connect your client to the Ruflo MCP server. Run the setup wizard in your project terminal:

npx ruflo@latest init wizard

For clients that support local stdio MCP servers, configure command npx and arguments ["-y", "ruflo@latest", "mcp", "start"]. The equivalent server command is:

npx -y ruflo@latest mcp start

MCP exposes Ruflo tools to your client. The console and mods above are Claude Code integrations; hook support depends on the client.

Compare install paths · Open the console · User guide

https://ruos.cognitum.one/mcp

npx ruvector

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.

_{Conceptual learning loop. Local vector retrieval and contrastive updates can run without an LLM; embeddings and configured learning modules are still required. See the RuVector training integration and trajectory contrastive learning.}

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.

Your agent cockpit. Track workflows, agents, models, tokens and cost beside Claude Code. The animation shows startup checks and a sample workflow, not a live session.

Inspect any run. Open agent logs and results, search, triage failures, replay and compare. Start with npx ruflo init, restart Claude Code, then /ruflo. Full console tour.

Let Claude drive. You set the limits. Enable Settings → Claude control to navigate and run console actions. Choose read, write, manage or full, with ask or auto approval. The current default is read + ask; raising the level is your choice. Actions above your permission level are refused, and network, spending and destructive actions require confirmation even in auto. Review the live action log or press Take back control to stop Claude control. Details.

One task: create a mission with Claude

Watch the recorded console session below. Claude creates a mission, opens the Learning and Security pages, and reports its actions in Overview.

1. Set the boundary. Install the console using the commands below, open /ruflo, then choose Settings → Claude control → write + ask.
2. Give a concrete request. Try: “Create a mission to add a dark mode toggle. Show me the mission and its status.”
3. Approve creation. Claude opens Missions and sets the goal. Confirm the pending create action in the console.
4. Verify the result. Check that Missions contains the goal and Overview records the action. Creating a mission does not mean the feature has been implemented.
5. Keep control. Take back control pauses Claude's console tools. A later call should be refused until you restore control.

What the recording demonstrates: a real Claude Haiku session with write + auto, mission creation, page navigation, a refused swarm stop, and control being taken back. The steps above use ask so you approve creation yourself. The separate workflow animation uses sample data; neither is evidence of completed swarm work or memory recall.

Implementation and recorded test findings · Reproduction script

Install the mods from the ruflo marketplace (Claude Code 2.1.287 or later; mods run with your account's permissions and are not sandboxed, so read the code first):

/plugin marketplace add ruvnet/ruflo
/plugin install ruflo-console@ruflo
/plugin install ruflo-mods@ruflo
/reload-plugins

ruflo-console is the cockpit above, ruflo-mods routes prompts and enforces policy in-process, ruflo-swarm shows the swarm in a pane, and ruflo-ruos adds the ruOS status segment. Open /plugin to confirm they appear in the active mods line. Inside the console, /ruflo market is the Plugin Catalog: every ruflo plugin, mod and skill with what it ships, and buttons to install, enable, disable and update (each asks first).

Quick Start

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

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

# 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.

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
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.

Learning from experience

Useful trajectories and task feedback can inform future work. Results depend on the configured memory, learning components and quality of feedback. Learning plugin.

Agent Federation — Slack for Agents

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.

# 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

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:

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

User Guide section index:

Support

License

MIT - RuvNet

{
  "name": "ruflo",
  "description": "RuFlo Marketplace: Claude Code native agents, swarms, workers, and MCP tools for continuous software engineering",
  "owner": {
    "name": "ruvnet",
    "url": "https://github.com/ruvnet"
  },
  "plugins": [
    {
      "name": "ruflo-core",
      "source": "./plugins/ruflo-core",
      "description": "Core Ruflo MCP tools, commands, and Claude Code orchestration patterns"
    },
    {
      "name": "ruflo-ai-team",
      "source": "./plugins/ruflo-ai-team/directory",
      "description": "Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results"
    },
    {
      "name": "ruflo-x-gateway",
      "source": "./plugins/ruflo-x-gateway/directory",
      "description": "Remote RuFlo Federation MCP connector for signed channels, work claims, evidence, and cross-agent coordination"
    },
    {
      "name": "ruflo-deepseek-harness",
      "source": "./plugins/ruflo-deepseek-harness",
      "description": "DeepSeek model harness with focused agents, commands, and skills for swarm-backed reasoning workflows"
    },
    {
      "name": "ruflo-swarm",
      "source": "./plugins/ruflo-swarm",
      "description": "Agent teams, swarm coordination, Monitor streams, and worktree isolation"
    },
    {
      "name": "ruflo-loop-workers",
      "source": "./plugins/ruflo-loop-workers",
      "description": "Cache-aware /loop workers and CronCreate background automation"
    },
    {
      "name": "ruflo-security-audit",
      "source": "./plugins/ruflo-security-audit",
      "description": "Security review, dependency scanning, policy gates, and CVE monitoring"
    },
    {
      "name": "ruflo-rag-memory",
      "source": "./plugins/ruflo-rag-memory",
      "description": "RuVector memory with HNSW search, AgentDB, and semantic retrieval"
    },
    {
      "name": "ruflo-testgen",
      "source": "./plugins/ruflo-testgen",
      "description": "Test gap detection, coverage analysis, and automated test generation"
    },
    {
      "name": "ruflo-docs",
      "source": "./plugins/ruflo-docs",
      "description": "Documentation generation, drift detection, and API docs automation"
    },
    {
      "name": "ruflo-autopilot",
      "source": "./plugins/ruflo-autopilot",
      "description": "Autonomous /loop-driven task completion with learning, prediction, and progress tracking"
    },
    {
      "name": "ruflo-intelligence",
      "source": "./plugins/ruflo-intelligence",
      "description": "Self-learning neural intelligence with SONA patterns, trajectory learning, and model routing"
    },
    {
      "name": "ruflo-agentdb",
      "source": "./plugins/ruflo-agentdb",
      "description": "AgentDB memory controllers with HNSW vector search, RuVector embeddings, and causal graphs"
    },
    {
      "name": "ruflo-aidefence",
      "source": "./plugins/ruflo-aidefence",
      "description": "AI safety scanning, PII detection, prompt injection defense, and adaptive threat learning"
    },
    {
      "name": "ruflo-protector",
      "source": "./plugins/ruflo-protector",
      "description": "Project Anatole: an optional, learning watchdog for unattended agents (OWASP-mapped rules, a per-project baseline, learn / notify / enforce modes). Default off."
    },
    {
      "name": "ruflo-browser",
      "source": "./plugins/ruflo-browser",
      "description": "Agentic browser automation with Playwright for testing, scraping, and UI interaction"
    },
    {
      "name": "ruflo-jujutsu",
      "source": "./plugins/ruflo-jujutsu",
      "description": "Advanced git workflows with diff analysis, risk scoring, and reviewer recommendations"
    },
    {
      "name": "ruflo-agent",
      "source": "./plugins/ruflo-agent",
      "description": "Agent runtimes — local WASM-sandboxed agents (rvagent) + Anthropic Claude Managed Agents (cloud); one interface, local-vs-cloud backends"
    },
    {
      "name": "ruflo-workflows",
      "source": "./plugins/ruflo-workflows",
      "description": "Visual workflow automation with templates, orchestration, and lifecycle management"
    },
    {
      "name": "ruflo-daa",
      "source": "./plugins/ruflo-daa",
      "description": "Dynamic Agentic Architecture with cognitive patterns, knowledge sharing, and adaptive agents"
    },
    {
      "name": "ruflo-ruvllm",
      "source": "./plugins/ruflo-ruvllm",
      "description": "RuVLLM local inference with chat formatting, MicroLoRA fine-tuning, and SONA adaptation"
    },
    {
      "name": "ruflo-rvf",
      "source": "./plugins/ruflo-rvf",
      "description": "RVF format for portable agent memory, session persistence, and cross-platform transfer"
    },
    {
      "name": "ruflo-plugin-creator",
      "source": "./plugins/ruflo-plugin-creator",
      "description": "Scaffold, validate, and publish new Claude Code plugins with proper structure"
    },
    {
      "name": "ruflo-goals",
      "source": "./plugins/ruflo-goals",
      "description": "Long-horizon goal planning, deep research orchestration, and adaptive replanning using GOAP"
    },
    {
      "name": "ruflo-adr",
      "source": "./plugins/ruflo-adr",
      "description": "ADR lifecycle management — create, index, supersede, and link Architecture Decision Records to code"
    },
    {
      "name": "ruflo-cost-tracker",
      "source": "./plugins/ruflo-cost-tracker",
      "description": "Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations"
    },
    {
      "name": "ruflo-ddd",
      "source": "./plugins/ruflo-ddd",
      "description": "Domain-Driven Design scaffolding — bounded contexts, aggregate roots, domain events, and anti-corruption layers"
    },
    {
      "name": "ruflo-federation",
      "source": "./plugins/ruflo-federation",
      "description": "Cross-installation agent federation with zero-trust security, PII-gated data flow, and compliance-grade audit trails"
    },
    {
      "name": "ruflo-graph-intelligence",
      "source": "./plugins/ruflo-graph-intelligence",
      "description": "Real-time graph intelligence — personalized PageRank, streaming delta updates, witness-signed reasoning, and federation-distributable vectors"
    },
    {
      "name": "ruflo-iot-cognitum",
      "source": "./plugins/ruflo-iot-cognitum",
      "description": "IoT device lifecycle, telemetry anomaly detection, fleet management, and witness chain verification for Cognitum Seed hardware"
    },
    {
      "name": "ruflo-knowledge-graph",
      "source": "./plugins/ruflo-knowledge-graph",
      "description": "Knowledge graph construction — entity extraction, relation mapping, and pathfinder graph traversal"
    },
    {
      "name": "ruflo-market-data",
      "source": "./plugins/ruflo-market-data",
      "description": "Market data ingestion — feed normalization, OHLCV vectorization, and HNSW-indexed pattern matching"
    },
    {
      "name": "ruflo-migrations",
      "source": "./plugins/ruflo-migrations",
      "description": "Schema migration management — generate, validate, dry-run, and rollback database migrations"
    },
    {
      "name": "ruflo-neural-trader",
      "source": "./plugins/ruflo-neural-trader",
      "description": "Neural trading strategies — self-learning LSTM/Transformer/N-BEATS models with Rust/NAPI backtesting"
    },
    {
      "name": "ruflo-observability",
      "source": "./plugins/ruflo-observability",
      "description": "Structured logging, distributed tracing, and metrics — correlate agent swarm activity with application telemetry"
    },
    {
      "name": "ruflo-ruvector",
      "source": "./plugins/ruflo-ruvector",
      "description": "Self-learning vector database — HNSW, FlashAttention-3, Graph RAG, hybrid search, DiskANN, and Brain AGI"
    },
    {
      "name": "ruflo-sparc",
      "source": "./plugins/ruflo-sparc",
      "description": "SPARC methodology — Specification, Pseudocode, Architecture, Refinement, Completion phases with quality gates"
    },
    {
      "name": "ruflo-metaharness",
      "source": "./plugins/ruflo-metaharness",
      "description": "MetaHarness integration — surfaces score/genome/mint/mcp-scan/threat-model via skills; pairs with @metaharness/router (ADR-148/149) for cost-optimal model routing; honors ADR-150 optional-augmentation constraint"
    },
    {
      "name": "ruflo-arena",
      "source": "./plugins/ruflo-arena",
      "description": "Competitive ruliology for ruflo swarms — arenas, tournaments, and adaptive co-evolution of program strategies (ADR-147/148); strategies-as-programs compete under payoff games"
    },
    {
      "name": "ruflo-agntcy",
      "source": "./plugins/ruflo-agntcy",
      "description": "AGNTCY/Outshift Internet-of-Cognition runtime integration — SLIM secure transport, CASA intent-scoped tool authorization, and AGNTCY identity/observability spans (ADR-380); optional, removable augmentation per ADR-150"
    },
    {
      "name": "ruflo-bbs-federation",
      "source": "./plugins/ruflo-bbs-federation",
      "description": "AgentBBS cross-host agent federation (ADR-164). Phase 1: register/publish/watch/human-join room coordination. Phase 2 (v3.40.0): signed cross-host federation — identity, peer_add (pin by nodeId+Ed25519 key), peers, serve (read-only pull), sync (pull + union-merge what verifies). Registry-anchored pinning; works on any network (no tailnet required); coordinates work claims (ClaimIssued/Released/Handoff/Ack). Degrades gracefully when agentbbs is absent."
    },
    {
      "name": "ruflo-business-pods",
      "source": "./plugins/ruflo-business-pods",
      "description": "Business-domain pod templates for the federated business autopilot (ADR-164 Phase 2) — pod templates plus a dry-run-by-default single-tick runner that validates, reserves budget, and resolves agent roles before posting to the BBS room"
    },
    {
      "name": "ruflo-music",
      "source": "./plugins/ruflo-music",
      "description": "AI music generation via Cognitum Music (cogmusic MCP) — compose lyrics/prompts, generate tracks, separate stems, extract MIDI, and master through your own music.cognitum.one account"
    },
    {
      "name": "ruflo-mods",
      "source": "./plugins/ruflo-mods",
      "description": "Early access (ADR-404): ruflo as a Claude Code mod (function hooks) — in-process routing, edit learning signals, tighten-only tool checks from ruflo policy, and the cost budget ladder. Opt-in via `ruflo mods install`; classic hooks stay the fallback"
    },
    {
      "name": "ruflo-ruos",
      "source": "./plugins/ruflo-ruos",
      "description": "Run ruflo swarm agents on your own ruOS cloud desktops via the tenant-authenticated fleet MCP or per-tenant SSH; optional, removable"
    },
    {
      "name": "ruflo-console",
      "source": "./plugins/ruflo-console",
      "description": "Early access: ruflo's cockpit as a Claude Code mod (function hooks) and the one /ruflo command for every ruflo mod — overview with health alerts, swarm topology, claims flow, federation map, plugin health, learning pipeline, MetaHarness radar, memory, cost gauge, agent timeline, approvals and events; a command palette for confirm-gated actions through the ruflo CLI; auto-opens where it docks; no network by default"
    }
  ]
}