Metro-MCP: Connect LLMs to real-time NYC & DC Metro data

Metro-MCP: Real-time NYC & DC Metro Data for AI Agents

Metro-MCP is a specialized MCP (Message Communication Protocol) tool designed to bridge the gap between Large Language Models (LLMs) and real-time public transportation data for the New York City and Washington D.C. metropolitan areas. This tool enables AI agents to access and process live information about train positions, estimated arrival times, and other critical transit updates, facilitating the development of sophisticated AI applications that can interact with and inform users about public transit status.

What it Does

Metro-MCP acts as an intermediary, fetching live data from the official NYC and DC Metro transit APIs. It then formats this data into a structured, machine-readable format that can be easily consumed by AI agents and LLMs. This allows developers to build agents capable of answering user queries about train schedules, delays, and current locations, or to integrate real-time transit information into broader AI workflows.

Key Features

• Real-time Data Access: Connects directly to live NYC and DC Metro transit feeds.
• Structured Data Output: Provides data in a format suitable for AI processing.
• MCP Integration: Designed to work seamlessly within the MCP framework for agent communication.
• Developer-Focused: Source code available on GitHub for customization and extension.
• Specific Transit Focus: Tailored for the unique data streams of NYC and DC subway and rail systems.

Who it's For

Metro-MCP is intended for AI developers and researchers building applications that require real-time public transportation data. This includes:

• Developers creating AI assistants for urban commuters.
• Teams building intelligent systems for transit management and optimization.
• Researchers exploring the integration of LLMs with real-world, time-sensitive data streams.
• Anyone looking to empower their AI agents with accurate, up-to-the-minute information about NYC and DC metro services.