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Gemini MCP File Agent (MVP)

Gemini MCP File Agent (MVP)

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github.com/kevingduckAI & Agents5Updated 77w ago

About Gemini MCP File Agent (MVP)

A local chat and MCP server example for testing Gemini file operations, aimed at developers exploring AI access to files. Read, write, and list actions are confined to a specified sandbox folder.

Key features

  1. 01Chat with Gemini through the command line
  2. 02Read, write, and list files
  3. 03Confine file operations to a sandbox
  4. 04Choose the sandbox directory

Use cases

  1. 01Ask Gemini to inspect files in the sandbox
  2. 02Create or read text files through chat

MCP support

The local MCP server provides the chat scripts with file-reading, writing, and listing operations within the sandbox.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Gemini MCP File Agent (MVP)

This project lets you chat with Google's Gemini AI and allow it to safely read, write, and list files on your computer within a specific, controlled folder (a "sandbox").

What it does:

  • mcp_server.py: A local server that Gemini uses to access files. You tell it which folder on your computer is the "sandbox."
  • Chat Scripts (chat_with_gemini_mcp.py, simple_chat.py): Command-line chats where you talk to Gemini. Gemini can then use the mcp_server.py to manage files in the sandbox.

USE WITH CAUTION: This is a basic example. Be careful about which folder you let the mcp_server.py access.

Quick Start

  1. Get Files: Make sure all .py files are in one folder.

  2. API Key:

    • Get a Google AI API Key from Google AI Studio.
    • Set it as an environment variable:
      export GOOGLE_API_KEY="YOUR_KEY_HERE" 
      
      (For Windows, use set GOOGLE_API_KEY="YOUR_KEY_HERE")
  3. Install Stuff:

    pip install -r requirements.txt 
    

    (Or run ./install_packages.sh)

  4. Run It:

    • Terminal 1: Start the MCP Server
      python mcp_server.py 
      
      (This creates & uses a ./mcp_data_sandbox/ folder by default. To use a different folder: python mcp_server.py --sandbox-dir ./my_files)
    • Terminal 2: Start Chatting
      python chat_with_gemini_mcp.py
      
  5. Chat with Gemini:

    • "What files are in my work folder?"
    • "Create notes.txt and write 'Hello world' in it."
    • "Read notes.txt."

How it Works (Simply)

  1. You chat with Gemini.
  2. If you ask about files, Gemini tells your chat script to use a "file tool."
  3. Your chat script tells the mcp_server.py to do the file action (read, write, etc.) in the sandbox folder.
  4. The server does it and tells the chat script the result.
  5. The chat script tells Gemini the result.
  6. Gemini tells you what happened.

Important

  • Sandbox Only: The mcp_server.py can ONLY touch files inside the folder you pick as the sandbox. This is for safety.
  • Local Use: Designed to be run on your own computer.

This is a basic tool to explore giving AI file access. Be smart about how you use it!

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