my-pal-mcp-server/README.md

Gemini MCP Server

A Model Context Protocol (MCP) server that enables integration with Google's Gemini models, optimized for Gemini 2.5 Pro Preview with 1M token context window.

Features

• Chat with Gemini: Send prompts to Gemini 2.5 Pro Preview by default
• Analyze Code: Process large codebases with Gemini's 1M token context window
• File Reading: Automatically read and analyze multiple files
• List Models: View all available Gemini models
• Configurable Parameters: Adjust temperature, max tokens, and model selection
• System Prompts: Support for system prompts to set context

Installation

1. Clone this repository
2. Create a virtual environment:

   python3 -m venv venv
   source venv/bin/activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

Configuration

Set your Gemini API key as an environment variable:

export GEMINI_API_KEY="your-api-key-here"

Usage

For Claude Desktop

Add this configuration to your Claude Desktop config file:

{
  "mcpServers": {
    "gemini": {
      "command": "/path/to/venv/bin/python",
      "args": ["/path/to/gemini_server.py"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Direct Usage

Run the server:

source venv/bin/activate
export GEMINI_API_KEY="your-api-key-here"
python gemini_server.py

Available Tools

chat

Send a prompt to Gemini and receive a response.

Parameters:

• prompt (required): The prompt to send to Gemini
• system_prompt (optional): System prompt for context
• max_tokens (optional): Maximum tokens in response (default: 8192)
• temperature (optional): Temperature for randomness 0-1 (default: 0.7)
• model (optional): Model to use (default: gemini-2.5-pro-preview-06-05)

analyze_code

Analyze code files or snippets with Gemini's massive context window. Perfect for when Claude hits token limits.

Parameters:

• files (optional): List of file paths to analyze
• code (optional): Direct code content to analyze
• question (required): Question or analysis request about the code
• system_prompt (optional): System prompt for context
• max_tokens (optional): Maximum tokens in response (default: 8192)
• temperature (optional): Temperature for randomness 0-1 (default: 0.3 for code)
• model (optional): Model to use (default: gemini-2.5-pro-preview-06-05)

Note: You must provide either files or code (or both).

list_models

List all available Gemini models that support content generation.

Usage Examples

From Claude Code

When working with large files in Claude Code, you can use the Gemini server like this:

1. Analyze a large file:

   Use the gemini tool to analyze this file: /path/to/large/file.py
   Question: What are the main design patterns used in this code?
   

2. Analyze multiple files:

   Use gemini to analyze these files together:
   - /path/to/file1.py
   - /path/to/file2.py
   - /path/to/file3.py
   Question: How do these components interact with each other?
   

3. Extended thinking with Gemini: When Claude hits token limits, you can pass the entire context to Gemini for analysis.

Models

The server defaults to gemini-2.5-pro-preview-06-05 which supports:

• 1 million token context window
• Advanced reasoning capabilities
• Code understanding and analysis

Other available models:

• gemini-1.5-pro-latest - Stable Gemini 1.5 Pro
• gemini-1.5-flash - Fast Gemini 1.5 Flash model
• gemini-2.0-flash - Gemini 2.0 Flash
• And many more (use list_models to see all available)

Requirements

• Python 3.8+
• Valid Google Gemini API key

Notes

• The Gemini 2.5 Pro preview models may have safety restrictions that block certain prompts
• If a model returns a blocked response, the server will indicate the finish reason
• The server estimates tokens as ~4 characters per token
• Maximum context window is 1 million tokens (~4 million characters)

Tips for Claude Code Users

1. When Claude says a file is too large, use the analyze_code tool with the file path
2. For architectural questions spanning multiple files, pass all relevant files to analyze_code
3. Use lower temperatures (0.1-0.3) for code analysis and higher (0.7-0.9) for creative tasks
4. The default model (2.5 Pro Preview) is optimized for large context understanding