puter-mcp
v0.1.1
Published
MCP server bridging LLM environments with Puter's free AI APIs
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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
npxcommand. - 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.
- Log in to puter.com.
- Open the browser Developer Tools (F12 or Cmd+Option+I) -> Console.
- Type
puter.authTokenand press Enter. - Copy the string (without quotes).
- 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
Clone the repository:
git clone https://github.com/yourusername/puter-mcp.git cd puter-mcpInstall dependencies:
npm installBuild the project:
npm run buildRun locally:
node bin/puter-mcp.mjs
License
MIT
