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