rails-mcp

Setting this up? Point your coding agent (Cursor, Claude Code, etc.) at llms.txt and ask it to self-configure rails-mcp in your project.

A Ruby gem that provides AI assistants with ruby code execution capabilities within the context of existing running application server. Think of it giving AI assistant lighting-speed access to ruby console without the need to write script, reload or restart.

Works with Rails, Sinatra, Hanami, Roda, and any other Rack-based framework. The code is executed in your application's context for debugging and investigation.

YouTube Link

Used at Apollo.io against a Rails codebase with 20k+ Ruby files.

1. Learn a new codebase or code areas quickly. With your AI client and a running server, you can ask it to research while executing snippets from your actual application code. It effectively acts as an in-loop code-verification block.
2. Perform quick, preliminary investigations of customer escalations using a read-only copy of the production environment. It can execute your application code, locate models, and run relevant class methods or code paths from the codebase to do preliminary root-cause analysis (RCA). Even better if your application uses an event-sourcing framework (i.e., change logs). The AI client, together with the code-execution capabilities via rails-mcp, can deliver fast preliminary RCAs.
3. Use it for quick data analytics and export reports as CSV.

Add this line to your application's Gemfile:

gem "rails-mcp"

Or install locally for development:

bundle install

Rails (config/routes.rb):

require "rails_mcp/mcp/server"

Rails.application.routes.draw do
  mount RailsMcp::MCP::Server.new => "/mcp"
end

Rack (config.ru):

require "rails_mcp"
require "rails_mcp/mcp/server"

map "/mcp" do
  run RailsMcp::MCP::Server.new
end

Sinatra:

require "rails_mcp/mcp/server"

mount RailsMcp::MCP::Server.new, at: "/mcp"

# Standalone with Rackup
bundle exec rackup -p 9292

# With Rails
bundle exec rails server

This gem ships without authentication — the MCP endpoint will accept any request that reaches it. You are responsible for ensuring it is only mounted where appropriate. A typical Rails setup gates it on environment:

Rails.application.routes.draw do
  mount RailsMcp::MCP::Server.new => "/mcp" if Rails.env.development?
end

For staging or production access, combine that with network-level restrictions (firewall, VPC, SSH port-forward, VPN) so the endpoint is never reachable from the open internet.

The MCP server exposes a single JSON-RPC endpoint:

• POST /mcp/rpc - JSON-RPC request and response

evaluate_ruby_code

• Description: Evaluates Ruby code and returns the result with captured stdout/stderr
• Parameters:
  • code (string, required): Ruby code to execute

Add to your MCP client configuration (.cursor/mcp.json for Cursor or claude_desktop_config.json for Claude Desktop):

{
  "mcpServers": {
    "rails-mcp": {
      "url": "http://localhost:3001/mcp/rpc"
    }
  }
}

For Claude Code, add it from the command line:

claude mcp add rails-mcp --transport http http://localhost:3001/mcp/rpc

Any MCP-compatible client can connect to the server by making JSON-RPC requests to the /mcp/rpc endpoint.

Example with curl:

curl -X POST "http://localhost:3001/mcp/rpc" \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/list"
  }'

Run the test suite:

bundle exec rspec

⚠️ This gem executes arbitrary Ruby code.

Important security considerations:

• No built-in authentication. Gate the mount on environment (e.g., if Rails.env.development?) so the endpoint isn't exposed in production by accident
• Only use in development environments or secure, isolated production environments
• Rely on network-level restrictions (firewall, VPC, SSH port-forward, VPN) to limit access
• Consider running in a sandboxed or containerized environment
• Monitor and log all code execution requests

This gem uses global $stdout/$stderr redirection during evaluation, which can clash in multi-threaded servers. For production use with concurrency, consider:

• Running in a single worker/thread mode
• Isolating evaluation per request (e.g., via fork)
• Using a dedicated job worker for code execution

MIT License - see LICENSE file for details.