An agent meta-harness for Claude Code and Codex.
Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y [email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add claude-flow -- npx -y claude-flow@3.77.1รันในเทอร์มินัล
{ "mcpServers": { "claude-flow": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}claude_desktop_config.json
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รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดStart 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.
Prefer a plain terminal? Optional. The console also runs on its own, with no Claude Code: npx ruflo tui (add --plain to print one frame for scripts). It shows Overview, Cost, Swarm, Events and Missions, plus an optional AI page. Terminal UI guide
Compare install paths · Open the console · User guide
Connect ruOS to ChatGPT or Claude via MCP:
https://ruos.cognitum.one/mcp
npx ruvector
📖 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.
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.
User → Ruflo (CLI/MCP) → Router → Swarm → Agents → Memory → LLM providers. Memory feeds useful experience back into routing. This is a conceptual flow, not a live execution trace.
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.
Built by Reuven Cohen (rUv), originally as Claude Flow. The first commit, June 2, 2025, describes a code orchestration layer for recursive agent cycles: Claude writes, edits, tests and improves. The June 10 source snapshot adds orchestration, task scheduling, memory and terminal modules.
A harness is the workbench around the model: it organizes tasks, carries context between steps and helps check results. This establishes Ruflo's lineage, not a universal first across every Claude Code tool. See the illustrated explainer, exact commits and earlier ecosystem context.
Grok Build: npx ruflo init --grok writes the project host surface (.grok/, the team bus, and the operator guide) and nothing outside the project; add --dry-run to preview. Setup, the spawn_subagent contract, the optional status row, and what to re-check when Grok updates: the Grok operator guide.
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 byCognitum.Oneagentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.
Your agent cockpit. Track workflows, agents, models, tokens and cost beside Claude Code. The 38 second animation shows Orbital and Theme Studio through actual renderer frames, including boot checks, six palettes, customization, saved themes, JSON import and resizing. This compact 3.84 MB SVG retains all 456 frames. Native host and AI provider execution are not demonstrated.
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.
Watch the recorded console session below. Claude creates a mission, opens the Learning and Security pages, and reports its actions in Overview.
/ruflo, then choose Settings → Claude control → write + ask.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 linked workflow animation uses sample data, while the theme demo replays renderer frames. 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).
There are two different install paths with very different surface areas. Pick based on what you need (#1744):
# 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.
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 ... | bashform needs a POSIX shell (Git-Bash, WSL, MSYS). Thenpx ruflo@latest init wizardline works natively in PowerShell and cmd. If you hit an'bash' is not recognizederror, use thenpxline instead — both end up running the same init flow.
# Add Ruflo as an MCP server in Claude Code
claude mcp add claude-flow -- npx ruflo@latest mcp start
Useful trajectories and task feedback can inform future work. Results depend on the configured memory, learning components and quality of feedback. Learning plugin.
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 atdocs/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)
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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)
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:
MIT - RuvNet
Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
{ "mcpServers": { "claude-flow": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Claude Flow ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-14 Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration