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puter-mcp

v0.1.1

Published

MCP server bridging LLM environments with Puter's free AI APIs

Downloads

189

Readme

puterMCP

A local MCP server that bridges LLM environments with Puter's free AI & Cloud services

puterMCP is a TypeScript/Node.js Model Context Protocol (MCP) server that runs locally via npx and acts as a bridge between any MCP-compatible LLM environment (Claude Desktop, Kilo Code, Trae, Cursor, Windsurf, etc.) and Puter's free, unlimited AI and Cloud APIs.

The first capability shipped is image generation across 30+ models (GPT Image, DALL-E, Gemini Nano Banana, Flux, Stable Diffusion, and more) — all without API keys or per-request costs.

Features

  • Zero Friction: Install and run with a single npx command.
  • Free Image Generation: Access 30+ models including DALL-E 3, Flux.1, and Stable Diffusion via Puter's free tier.
  • Secure Authentication: Uses your personal Puter account token, stored locally and securely.
  • Universal Compatibility: Works with Claude Desktop, Cursor, Trae, and any other MCP client.
  • Inline Image Generation: Images are returned directly in the chat interface, ready for preview and download.
  • Smart Fallback: Automatically tries free models (like Flux) if premium models (like DALL-E 3) fail due to quota limits.

Prerequisites

Installation & Setup

1. Authenticate with Puter

You need to provide your Puter authentication token to the MCP server. This is a one-time setup.

  1. Log in to puter.com.
  2. Open the browser Developer Tools (F12 or Cmd+Option+I) -> Console.
  3. Type puter.authToken and press Enter.
  4. Copy the string (without quotes).
  5. Run the following command in your terminal:
npx puter-mcp --token <your-token-here>

Your token will be securely stored in ~/.puter-mcp/config.json.

2. Configure Your MCP Client

Claude Desktop

Add the following to your claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "puter": {
      "command": "npx",
      "args": ["-y", "puter-mcp"]
    }
  }
}

Trae / Cursor / Kilo Code

Add the configuration to your project's MCP settings (e.g., .kilo/mcp.json or via the IDE settings UI):

{
  "mcpServers": {
    "puter": {
      "command": "npx",
      "args": ["-y", "puter-mcp"]
    }
  }
}

Usage

Once configured, restart your LLM environment. You can now ask it to generate images:

  • "Generate a cyberpunk city at night using DALL-E 3"
  • "Create a logo for a coffee shop using Flux.1 Schnell"
  • "Show me what models are available"

Available Tools

  • generate_image: Generate an image from a text prompt.

    • prompt: Description of the image.
    • model: (Optional) Model ID (default: dall-e-3).
    • quality: (Optional) Quality setting (e.g., hd, standard).
  • list_models: List all available image generation models.

    • category: (Optional) Filter by category (all, openai, google, flux, stable-diffusion, other).

Development

  1. Clone the repository:

    git clone https://github.com/yourusername/puter-mcp.git
    cd puter-mcp
  2. Install dependencies:

    npm install
  3. Build the project:

    npm run build
  4. Run locally:

    node bin/puter-mcp.mjs

License

MIT