BundlerMCP
Query information about dependencies in a Ruby project's Gemfile.
BundlerMCP
A Model Context Protocol (MCP) server enabling AI agents to query information about dependencies in a Ruby project's Gemfile. Built with fast-mcp.
Installation
Install the gem and add to the application's Gemfile by executing:
bundle add bundler_mcp --group=development
Usage
- Generate the binstub:
bundle binstubs bundler_mcp
- Configure your client to execute the binstub. Here are examples that work for Claude and Cursor:
Basic Example (mcp.json)
{
"mcpServers": {
"bundler-mcp": {
"command": "/Users/mike/my_project/bin/bundler_mcp"
}
}
}
Example with logging and explicit Gemfile
{
"mcpServers": {
"bundler-mcp": {
"command": "/Users/mike/my_project/bin/bundler_mcp",
"env": {
"BUNDLER_MCP_LOG_FILE": "/Users/mike/my_project/log/mcp.log",
"BUNDLE_GEMFILE": "/Users/mike/my_project/subdir/Gemfile"
}
}
}
}
Documentation
Available Tools
The server provides two tools for AI agents:
list_project_gems
Lists all bundled Ruby gems with their:
- Versions
- Descriptions
- Installation paths
- Top-level documentation locations (e.g.
READMEandCHANGELOG)

get_gem_details
Retrieves detailed information about a specific gem, including:
- Version
- Description
- Installation path
- Top-level documentation locations
- Source code file locations

Environment Variables
BUNDLE_GEMFILE: Used by Bundler to locate your Gemfile. If you use the binstub method described in the Usage section, this is usually not needed.BUNDLER_MCP_LOG_FILE: Path to log file. Useful for troubleshooting (defaults to no logging)
Development
After checking out the repo, run bin/setup to install dependencies and bundle exec rspec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.
Testing with the MCP Inspector
You can test the server directly using the MCP inspector:
# Basic usage
npx @modelcontextprotocol/inspector ./bin/bundler_mcp
# With logging enabled
BUNDLER_MCP_LOG_FILE=/tmp/log/mcp.log npx @modelcontextprotocol/inspector ./bin/bundler_mcp
# With custom Gemfile
BUNDLE_GEMFILE=./other/Gemfile npx @modelcontextprotocol/inspector ./bin/bundler_mcp
Release Process
To install this gem onto your local machine, run bundle exec rake install. To release a new version:
- Update the version number in
version.rb - Run
bundle exec rake release
This will:
- Create a git tag for the version
- Push git commits and the created tag
- Push the
.gemfile to rubygems.org
Contributing
Bug reports and pull requests are welcome on GitHub at https://github.com/subelsky/bundler_mcp.
License
Open source under the terms of the MIT License.
Author
関連サーバー
Scout Monitoring MCP
スポンサーPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
スポンサーAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Scientific Computation MCP
Provides tools for scientific computation, including tensor storage, linear algebra, vector calculus, and visualization.
Storybook MCP
Help agents automatically write and test stories for your UI components
Chrome DevTools MCP
chrome-devtools-mcp lets your coding agent (such as Gemini, Claude, Cursor or Copilot) control and inspect a live Chrome browser
TouchDesigner MCP
Control and operate TouchDesigner projects with AI agents using the Model Context Protocol.
Pica MCP Server
Integrates with the Pica API platform to interact with various third-party services through a standardized interface.
Drupal Modules MCP
Retrieve detailed information about Drupal modules from drupal.org, including version compatibility, installation instructions, and documentation.
Slowtime MCP Server
A server for secure time-based operations, featuring timing attack protection and timelock encryption.
Mobile Xray MCP
Take screenshots and analyze mobile apps with AI assistance directly from your IDE.
browser-devtools-mcp
A Playwright-based MCP server that exposes a live browser as a traceable, inspectable, debuggable and controllable execution environment for AI agents.
Tuteliq
AI-powered safety tools for detecting grooming, bullying, threats, and harmful interactions in conversations. The server integrates Tuteliq’s behavioral risk detection API via the Model Context Protocol (MCP), enabling AI assistants to analyze interaction patterns rather than relying on keyword moderation. Use cases include platform safety, chat moderation, child protection, and compliance with regulations such as the EU Digital Services Act (DSA), COPPA, and KOSA.