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