fal

fal MCP Server

A Model Context Protocol (MCP) server for interacting with fal.ai models and services. This project was inspired by am0y's MCP server, but updated to use the latest streaming MCP support.

Features

• List all available fal.ai models
• Search for specific models by keywords
• Get model schemas
• Generate content using any fal.ai model
• Support for both direct and queued model execution
• Queue management (status checking, getting results, cancelling requests)
• File upload to fal.ai CDN
• Full streaming support via HTTP transport

Requirements

• Python 3.12+
• fastmcp
• httpx
• aiofiles
• A fal.ai API key

Installation

1. Clone this repository:

2. Install the required packages:

Usage

Running the Server Locally

1. Get your fal.ai API key from fal.ai
2. Start the MCP server with HTTP transport:

The server will start and display connection information in your terminal.

3. Connect to it from your LLM IDE (Claude Code or Cursor) by adding to your configuration:

Development Mode (with MCP Inspector)

For testing and debugging, you can run the server in development mode:

This will:

• Start the server on a random port
• Launch the MCP Inspector web interface in your browser
• Allow you to test all tools interactively with a web UI

The Inspector URL will be displayed in the terminal (typically http://localhost:PORT).

Environment Variables

The run_http.sh script automatically handles all environment variables for you. If you need to customize:

• PORT: Server port for HTTP transport (default: 6274)

Setting API Key Permanently

If you prefer to set your API key permanently instead of passing it each time:

1. Create a .env file in the project root:

2. Then run the server without the API key argument:

For manual setup:

• FAL_KEY: Your fal.ai API key (required)
• MCP_TRANSPORT: Transport mode - stdio (default) or http

Available Tools

• models(page=None, total=None) - List available models with optional pagination
• search(keywords) - Search for models by keywords
• schema(model_id) - Get OpenAPI schema for a specific model
• generate(model, parameters, queue=False) - Generate content using a model
• result(url) - Get result from a queued request
• status(url) - Check status of a queued request
• cancel(url) - Cancel a queued request
• upload(path) - Upload a file to fal.ai CDN

License

MIT