Claude Flow

Name: Claude Flow
Author: ruvnet

by ruvnetversion 2.0.0-alpha.107i★ –iRuns on your computer

Registry nameio.github.ruvnet/claude-flow

Install

Overview

Description from the maker (original English)

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other
You need to fill in: ANTHROPIC_API_KEY, GITHUB_TOKEN, FLOW_NEXUS_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: ANTHROPIC_API_KEY, CLAUDE_FLOW_MODE, CLAUDE_FLOW_MEMORY_PATH, CLAUDE_FLOW_MAX_AGENTS, CLAUDE_FLOW_PORT, GITHUB_TOKEN, FLOW_NEXUS_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "claude-flow": {
      "command": "npx",
      "args": [
        "-y",
        "claude-flow"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "CLAUDE_FLOW_MODE": "your-value",
        "CLAUDE_FLOW_MEMORY_PATH": "your-value",
        "CLAUDE_FLOW_MAX_AGENTS": "your-value",
        "CLAUDE_FLOW_PORT": "your-value",
        "GITHUB_TOKEN": "your-value",
        "FLOW_NEXUS_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add claude-flow --env ANTHROPIC_API_KEY=your-value --env CLAUDE_FLOW_MODE=your-value --env CLAUDE_FLOW_MEMORY_PATH=your-value --env CLAUDE_FLOW_MAX_AGENTS=your-value --env CLAUDE_FLOW_PORT=your-value --env GITHUB_TOKEN=your-value --env FLOW_NEXUS_API_KEY=your-value -- npx -y claude-flow

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "claude-flow": {
      "command": "npx",
      "args": [
        "-y",
        "claude-flow"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "CLAUDE_FLOW_MODE": "your-value",
        "CLAUDE_FLOW_MEMORY_PATH": "your-value",
        "CLAUDE_FLOW_MAX_AGENTS": "your-value",
        "CLAUDE_FLOW_PORT": "your-value",
        "GITHUB_TOKEN": "your-value",
        "FLOW_NEXUS_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "claude-flow": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "claude-flow"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "CLAUDE_FLOW_MODE": "your-value",
        "CLAUDE_FLOW_MEMORY_PATH": "your-value",
        "CLAUDE_FLOW_MAX_AGENTS": "your-value",
        "CLAUDE_FLOW_PORT": "your-value",
        "GITHUB_TOKEN": "your-value",
        "FLOW_NEXUS_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

ANTHROPIC_API_KEY secret env
Anthropic API key for Claude AI models
CLAUDE_FLOW_MODE env
Operation mode: development, production, or test
CLAUDE_FLOW_MEMORY_PATH env
Path for persistent memory storage
CLAUDE_FLOW_MAX_AGENTS env
Maximum number of concurrent agents
CLAUDE_FLOW_PORT env
MCP server port
GITHUB_TOKEN secret env
GitHub personal access token for repository operations
FLOW_NEXUS_API_KEY secret env
Flow Nexus cloud platform API key

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account ruvnet, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32602 servers in this category
Published to the registry more recently than 0% of the other 32602 servers in this category
Basic checks equal to or better than 100% of the other 32602 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Claude Flow safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: ANTHROPIC_API_KEY, GITHUB_TOKEN, FLOW_NEXUS_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.0.0-alpha.107) reached the registry 14 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Rystic

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Remote Desktop Commander

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Rystic

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Start, seed, clock, inspect and diff Rystic API simulators from your agent.

Runs on your computerUpdated today

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

An agent meta-harness for Claude Code and Codex.

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

From a terminal on Claude Code 2.1.292 or later, one command adds the marketplace and installs a plugin: claude plugin install ruflo-core@ruflo --marketplace ruvnet/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

Optional: ruOS Desktop

Connect ruOS to ChatGPT or Claude via MCP:

https://ruos.cognitum.one/mcp

npx ruvector

Ruflo

English · 简体中文

[📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves](docs/ruflo-explained.md) 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 .

Architecture in text

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 406 MCP tools or 61 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.

An origin you can inspect

Built by [Reuven Cohen (rUv)](https://github.com/ruvnet), 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.

📖 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.

Open animated demo · Theme Studio guide · Workflow demo

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.

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.

Set the boundary. Install the console using the commands below, open /ruflo, then choose Settings → Claude control → write + ask.
Give a concrete request. Try: “Create a mission to add a

Only the beginning is shown; read the rest in the repo

Claude Flow

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Rystic

README from the maker

Get started with Ruflo

Optional: ruOS Desktop

Ruflo

An origin you can inspect

One task: create a mission with Claude