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
- 01Chat with Gemini through the command line
- 02Read, write, and list files
- 03Confine file operations to a sandbox
- 04Choose the sandbox directory
Use cases
- 01Ask Gemini to inspect files in the sandbox
- 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.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGemini 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 themcp_server.pyto 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
-
Get Files: Make sure all
.pyfiles are in one folder. -
API Key:
- Get a Google AI API Key from Google AI Studio.
- Set it as an environment variable:
(For Windows, useexport GOOGLE_API_KEY="YOUR_KEY_HERE"set GOOGLE_API_KEY="YOUR_KEY_HERE")
-
Install Stuff:
pip install -r requirements.txt(Or run
./install_packages.sh) -
Run It:
- Terminal 1: Start the MCP Server
(This creates & uses apython mcp_server.py./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
- Terminal 1: Start the MCP Server
-
Chat with Gemini:
- "What files are in my work folder?"
- "Create
notes.txtand write 'Hello world' in it." - "Read
notes.txt."
How it Works (Simply)
- You chat with Gemini.
- If you ask about files, Gemini tells your chat script to use a "file tool."
- Your chat script tells the
mcp_server.pyto do the file action (read, write, etc.) in the sandbox folder. - The server does it and tells the chat script the result.
- The chat script tells Gemini the result.
- Gemini tells you what happened.
Important
- Sandbox Only: The
mcp_server.pycan 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!
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.