Fal AI MCP Server

Name: Fal AI MCP Server
Author: piebro

@piebro

リポジトリ

Fal AI MCP Server について

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

#mcp #generative-ai #mcp-server

基本情報

カテゴリ

その他

ライセンス

MIT license

ランタイム

python

トランスポート

stdio

公開者

piebro

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "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"
      }
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.