Fal AI MCP Server

Name: Fal AI MCP Server
Author: piebro

@piebro

Repository

About Fal AI MCP Server

An MCP (Model Context Protocol) Server to use the fal.ai APIs to generate images and videos.

#mcp #generative-ai #mcp-server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "fal-ai-mcp-server-piebro": {
      "name": "fal-ai-mcp-server",
      "command": "uvx",
      "args": [
        "fal-ai-mcp-server"
      ],
      "env": {
        "FAL_KEY": "your-key",
        "SAVE_MEDIA_DIR": "path/to/save/images"
      }
    }
  }
}

Tools

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Overview

What is Fal AI MCP Server?

An MCP (Model Context Protocol) server that uses fal.ai APIs to generate images and videos. It is a barebones, extendable server intended for developers integrating fal.ai models and API endpoints into MCP-based workflows.

How to use Fal AI MCP Server?

Install uv, then add the server to your MCP client’s config using uvx with the FAL_KEY and SAVE_MEDIA_DIR environment variables. Alternatively, clone the repository and use uv with a directory. The server runs as an MCP tool provider.

Key features of Fal AI MCP Server

Generates images and videos via fal.ai APIs.
Compatible with any MCP client.
Barebones design for easy extension.
Requires a valid FAL_KEY for authentication.
Saves generated media to a configurable directory.
Can be run via uvx or directly with uv.

Use cases of Fal AI MCP Server

Quickly generate images or videos within an MCP‑based agent.
Integrate fal.ai models into existing MCP toolchains.
Extend the server to support additional fal.ai API endpoints.
Prototype AI media generation without building a custom client.

FAQ from Fal AI MCP Server

What is the Fal AI MCP Server?

It is an MCP server that acts as a bridge to fal.ai’s image and video generation APIs. It is designed to be minimal and easily customized for different fal.ai models.

What prerequisites do I need to run it?

You need Python, the uv package manager, and a valid FAL_KEY from fal.ai. Optionally, set SAVE_MEDIA_DIR to specify where media files will be stored.

How do I configure the server in my MCP client?

Add a JSON entry to your MCP client’s config with the command uvx and arguments fal-ai-mcp-server, plus the required environment variables FAL_KEY and SAVE_MEDIA_DIR. Alternatively, point uv to a cloned repository directory.

Can I test the server without a full MCP client?

Yes, the README recommends using mcp-client-for-testing with uvx. An example command is provided that calls an echo tool to verify the server is working.

Is there a way to extend the server to use other fal.ai models?

Yes, the README explicitly states it is a barebones server that anyone can extend to use different fal.ai models and API endpoints.

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