Fal AI MCP Server

@piebro

Repository

Basic information

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

Fal AI MCP Server 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"
      }
    }
  }
}

Fal AI MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

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.

Frequently asked questions

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.

Comments

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