What is Ai Pair Programmer Mcp

The AI Pair Programmer MCP Server is a Ruby implementation designed to provide AI-powered tools that assist developers in various aspects of coding, such as code review, brainstorming, performance analysis, and security review, leveraging a Model Context Protocol (MCP) framework.

Use cases

This server can be utilized for comprehensive code reviews, generating actionable feedback, enabling creative brainstorming sessions, conducting performance analyses to optimize code efficiency, and performing security assessments to detect potential vulnerabilities in code.

How to use

To use the server, set up the environment by installing the required Ruby version and obtaining an OpenRouter API key. Configure the server by exporting the API key as an environment variable and running the server script. Connect your MCP client, like Claude Desktop, by adding the server command configuration. You can then interact with the server using specific prompts for different functionalities.

Key features

The server supports multiple AI models via OpenRouter, with Gemini being the default. It provides tools for collaboration, code review, performance analysis, and security checks. The server features automatic gem installation and logging capabilities, facilitating easy setup and integration.

Where to use

The server can be deployed in developer environments where collaboration, code quality assessments, and security practices are necessary. It is suitable for teams working on Ruby projects, offering them AI-driven insights to improve their coding processes and ensure robust application security.

AI Pair Programmer MCP Server (Ruby)

A Ruby implementation of an AI Pair Programmer MCP (Model Context Protocol) server that provides AI-powered tools for code review, brainstorming, performance analysis, and security review.

Features

This server provides 5 AI-powered tools:

1. pair - General collaboration and problem-solving
2. review - Comprehensive code review with actionable feedback
3. brainstorm - Creative ideation and solution exploration
4. review_performance - Performance analysis and optimization suggestions
5. review_security - Security-focused code review and vulnerability detection

Installation & Setup

Prerequisites

• Ruby 3.0+
• An OpenRouter API key

Automatic Installation

The server uses inline bundler for automatic gem installation. Required gems:

• fast-mcp - Ruby MCP server framework
• ruby_llm - Unified AI model interface

Configuration

1. Set your OpenRouter API key:

export OPENROUTER_API_KEY="your_api_key_here"

Running the Server

ruby ./server.rb

The server will:

• Automatically install missing gems on first run
• Start with STDIO transport for MCP clients
• Log to STDERR which should be saved by your MCP Host.

If the MCP fails to start when lunching Claude Code it’s probably due to timeout.
The bundler is installing dependecies. To fix that either set an envvar MCP_TIMEOUT=10000 (10s) or start the MCP server in the terminal first.

Configuration

Models

The server supports these AI models via OpenRouter:

• Gemini (default) - google/gemini-2.5-pro-preview
• O3 - openai/o3
• Grok - x-ai/grok-3-beta
• DeepSeek - deepseek/deepseek-r1-0528
• Opus - anthropic/claude-opus-4

MCP Client Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "AiPairProgrammer": {
      "command": "ruby",
      "args": [
        "/path/to/server.rb"
      ]
    }
  }
}

Usage Examples

Once connected to an MCP client:

Code Review

Please review this Ruby code for best practices and potential issues:

def process_data(items)
  items.map { |item| item.upcase }
end

Performance Analysis

Can you analyze this code for performance bottlenecks?

def find_duplicates(array)
  duplicates = []
  array.each do |item|
    if array.count(item) > 1 && !duplicates.include?(item)
      duplicates << item
    end
  end
  duplicates
end

Security Review

Please check this authentication code for security vulnerabilities:

def authenticate(username, password)
  user = User.find_by(username: username)
  if user && user.password == password
    session[:user_id] = user.id
    true
  else
    false
  end
end

Brainstorming

I need ideas for improving user onboarding in my Ruby on Rails app. The current flow has a 60% drop-off rate.

General Collaboration

I'm struggling with this algorithm problem. Can you help me think through it step by step?

Architecture

The server is built with:

• FastMcp - Ruby MCP server framework with STDIO transport
• RubyLLM - Unified interface to AI models via OpenRouter
• Inline Bundler - Automatic gem installation for easy deployment

License

MIT License

Prior work:

AI Assistant MCP Server by Eduard
https://github.com/eduardm/ai_pairs_with_ai

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test with ruby test_server.rb
5. Submit a pull request