API Development stdio

FLUJO

Name: FLUJO
Author: punkpeye

Created by punkpeye

Orchestrates automated workflows by connecting AI models with various tools and resources using MCP.

How to Connect & Install

Select your client or environment below to copy the verified, ready-to-run installation configuration.

1-line autonomous agent setup instruction. Paste into Claude Code, Codex CLI, or Cursor Agent:

Fetch and configure Model Context Protocol (MCP) server FLUJO from https://www.fastmcp.dev/server/flujo

Agents automatically discover, install, and execute the server spec without manual token setup.

Connect via direct Stateless MCP v2 / Streamable HTTP endpoint or JSON-RPC:

https://www.fastmcp.dev/mcp

Stateless edge endpoint compliant with MCP 2024-11-05 and v2 draft protocol specs.

Includes server instructions and tool definitions for Claude:

claude mcp add flujo -- npx -y flujo

Run in terminal to register server in current project or pass --scope user for global availability.

Configures server instructions and tools for OpenAI Codex & ChatGPT Desktop:

[mcp_servers.flujo]
command = "npx"
args = ["-y","flujo"]

Applies to ChatGPT Desktop app, Codex CLI, and IDE extension across your Codex host.

Add to Cursor project settings (.cursor/mcp.json) or Cursor Settings > Features > MCP:

{
  "mcpServers": {
    "flujo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "flujo-1"
      ]
    }
  }
}

Commit to version control to allow teammates to connect immediately.

Install as an autonomous Agent Skill using the standard skills CLI:

npx skills add https://github.com/flujo-ai/flujo

Standard agent skill installer compatible with Claude Code, Cursor, and agy harnesses.

Server Guidance & Instructions OpenAI & Claude Spec Compliant

FLUJO: Orchestrates automated workflows by connecting AI models with various tools and resources using MCP.

Codex and Claude read this instruction prompt during initialization to orchestrate cross-tool workflows and rate limits.

Top Core Functions

01 Connect AI models with resources

02 Automate complex task execution workflows

03 Integrate tools through MCP interface