Gemini FAF

MCP server · by one

AI & ML Python v3.0.0

Persistent project context for Google Gemini. Python/FastMCP. IANA-registered .faf format.

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Install

Run one of the commands below, then add the client config underneath.

Pythonuvx gemini-faf-mcp

Client configuration

Paste into Claude Desktop, Cursor (mcp.json), VS Code or any MCP client, then restart the client.

mcpServers{
  "mcpServers": {
    "gemini-faf-mcp-2": {
      "command": "uvx",
      "args": [
        "gemini-faf-mcp"
      ]
    }
  }
}

About this server

Gemini FAF is listed in the AI & ML category of the MCPNav directory. It is distributed as Python and can be loaded by any client that speaks the Model Context Protocol.

Typical uses include giving your assistant scoped access to the corresponding service so it can answer questions and take actions with real data instead of guessing. Always review what a server can access before you enable it — see our MCP security guide.

Frequently asked questions

What is the Gemini FAF MCP server?

Gemini FAF is an MCP server by one. Persistent project context for Google Gemini. Python/FastMCP. IANA-registered .faf format.

How do I install Gemini FAF?

Install it with: uvx gemini-faf-mcp. Then add the JSON config to your client's MCP settings and restart the client.

Is Gemini FAF free to use?

The MCP server itself is free to install. The source is public on https://github.com/Wolfe-Jam/gemini-faf-mcp. Any third-party API it calls (such as a search or maps API) may require its own key and billing.

Which clients support Gemini FAF?

Any MCP-compatible client can use it, including Claude Desktop, Cursor, VS Code, Windsurf and custom agents.