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.
@piebro
基本信息
An MCP (Model Context Protocol) Server to use the fal.ai APIs to generate images and videos.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"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"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
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.
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.
FAL_KEY for authentication.uvx or directly with uv.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.
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.
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.
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.
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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