PuterMCP

Status: This project is no longer actively maintained.

Reason: Puter's API is designed for browser-based usage via Puter.js. Server-side direct API calls hit rate limits and cannot be used reliably. The official Puter.js library requires Node.js 24+, which is not widely available.

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Historical: A local MCP server that bridged 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

• Node.js (v18 or higher)
• A free account on Puter.com

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

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Alternatives

If you need free image generation in your MCP/AI workflows, consider:

1. OpenRouter - Free tier available with various image models
2. Together.ai - Free tier with Flux models (10 req/min)
3. Direct API keys - Use OpenAI, Google, or Anthropic APIs with your own keys

For browser-based applications, the official Puter.js library works well and supports image generation directly from frontend code.