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Gemini MCP File Agent (MVP)

@kevingduck

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

kevingduck

About Gemini MCP File Agent

Simple chat interface and server for testing Gemini MCP

#gemini#mcp#file-agent

Gemini MCP File Agent config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "gemini_mcp": {
      "command": "python",
      "args": [
        "mcp_server.py"
      ]
    }
  }
}

Gemini MCP File Agent tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Gemini MCP File Agent (MVP)?

It is a local server and chat scripts that allow Google's Gemini AI to safely read, write, and list files on your computer within a specific, controlled folder (a sandbox). It is intended for developers exploring AI file access.

How to use Gemini MCP File Agent (MVP)?

Install the Python packages, set your Google AI API key as the GOOGLE_API_KEY environment variable, then run mcp_server.py (optionally with --sandbox-dir) in one terminal and chat_with_gemini_mcp.py in another. You can then ask Gemini about files in the sandbox.

Key features of Gemini MCP File Agent (MVP)

  • Safe file access limited to a sandbox folder.
  • Command-line chat interface with Gemini.
  • Can read, write, and list files.
  • Uses a local MCP server (mcp_server.py).
  • Designed for local, single‑computer use.

Use cases of Gemini MCP File Agent (MVP)

  • Ask Gemini what files are in your work folder.
  • Have Gemini create a file and write content to it.
  • Have Gemini read the contents of an existing file.
  • Explore giving an AI controlled file access.

Frequently asked questions

1

What is the sandbox?

The sandbox is a specific folder you choose (default: `./mcp_data_sandbox/`). The server can only touch files inside that folder for safety.

2

Why do I need an API key?

You need a Google AI API key from Google AI Studio to use Gemini. Set it as the environment variable `GOOGLE_API_KEY`.

3

Can Gemini access files outside the sandbox?

No. The `mcp_server.py` is designed to only access files inside the folder you pick as the sandbox.

4

How do I use a different sandbox folder?

Run `python mcp_server.py --sandbox-dir ./my_files` to use a custom folder instead of the default `./mcp_data_sandbox/`.

5

Is this safe for production use?

No. The README states this is a basic example and cautions you to be careful about which folder the server accesses.

Comments

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