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Fal AI MCP Server

@piebro

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT license

トランスポート

stdio

作者

piebro

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

Fal AI MCP Server の設定

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"
      }
    }
  }
}

Fal AI MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

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.

よくある質問

1

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.

2

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.

3

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.

4

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.

5

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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