Gemini Agent MCP Server

Gemini Agent MCP Server

Provides a Model Context Protocol interface to the Gemini CLI, enabling AI agents to call the Gemini model and interact with development tools like code linting, GitHub operations, and documentation generation. Includes security measures to prevent unauthorized file access through path validation.

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README

Gemini CLI Agent MCP Server

This project is a Python-based FastMCP server that provides a Model Context Protocol (MCP) interface to the Gemini CLI and other development tools. It allows AI agents and other systems to programmatically call the Gemini model and perform various development tasks.

Key Technologies

  • Python
  • FastMCP

Features

The server exposes a set of tools to interact with the Gemini CLI and perform development tasks:

  • call_gemini: Calls the Gemini CLI with a given prompt. The Gemini CLI itself handles @-mentions of files and directories.
  • create_github_issue: Creates a new issue in a GitHub repository.
  • create_github_pr: Creates a new pull request in a GitHub repository.
  • summarize_docs: Summarizes the content of a list of documentation files.
  • generate_docstrings: Generates docstrings for functions or classes in a given file.
  • analyze_dependencies: Analyzes a dependency file (requirements.txt or package.json) and provides a summary of each dependency.
  • lint_code: Lints a Python or JavaScript file and returns a report of issues.
  • generate_unit_tests: Generates unit tests for a given function or class in a file.

Getting Started

Prerequisites

  • Python 3.x
  • pip

Installation

  1. Install the dependencies:
    pip install -r requirements.txt
    

Running the Server

python src/app.py

The server will start on 0.0.0.0:8000 by default.

Development

Conventions

  • Code Style: This project uses pylint for Python linting.
  • Dependencies: Project dependencies are managed in requirements.txt.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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