mcp-fal

mcp-fal is a Model Context Protocol (MCP) server designed for interacting with fal.ai models and services. Implemented in Python, this tool provides an API for leveraging various AI models. Users can list available models, search for specific models by keywords, retrieve model schemas, and generate content using these models. It supports both direct execution and queued execution, along with the ability to upload files to the fal.ai CDN. This makes it easy for developers to integrate AI models and utilize them in various applications.

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README
fal.ai MCP Server

A Model Context Protocol (MCP) server for interacting with fal.ai models and services.

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
Requirements
  • Python 3.10+
  • fastmcp
  • httpx
  • aiofiles
  • A fal.ai API key
Installation
  1. Clone this repository:
git clone https://github.com/am0y/mcp-fal.git
cd mcp-fal
  1. Install the required packages:
pip install fastmcp httpx aiofiles
  1. Set your fal.ai API key as an environment variable:
export FAL_KEY="YOUR_FAL_API_KEY_HERE"
Usage
Running the Server

You can run the server in development mode with:

fastmcp dev main.py

This will launch the MCP Inspector web interface where you can test the tools interactively.

Installing in Claude Desktop

To use the server with Claude Desktop:

fastmcp install main.py -e FAL_KEY="YOUR_FAL_API_KEY_HERE"

This will make the server available to Claude in the Desktop app.

Running Directly

You can also run the server directly:

python main.py
API Reference
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

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