A high-performance transit integration providing real-time New York City subway and bus data directly to your AI agent.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mta
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install mta using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is NYC MTA Transit?
The NYC MTA Transit skill empowers your agent with live data from the New York City Metropolitan Transportation Authority. It covers everything from real-time subway arrivals using GTFS-RT protobuf feeds to bus predictions via the SIRI JSON API. This tool is essential for developers building travel-aware agents within the Openclaw Skills ecosystem, offering deep visibility into the world's most complex transit system.
Whether you need to check for weekend service changes, find the nearest subway entrance, or track a specific M15 bus, this skill provides the technical plumbing required for accurate transit assistance. It handles the complexity of multiple data formats and endpoints, translating raw transit telemetry into actionable insights for the user while maintaining a lightweight footprint.
NYC MTA Transit Use Cases
- Monitoring real-time subway arrivals for specific lines like the 1/2/3, A/C/E, or N/Q/R/W.
- Checking for active service alerts, delays, and planned maintenance across the entire MTA network.
- Retrieving live bus arrival predictions and vehicle locations using an MTA API key.
- Finding nearby transit stops based on geographic coordinates or fuzzy station name matching.
- Comparing MTA fares and identifying payment options like OMNY and MetroCard for commuters.
How NYC MTA Transit Works
- The skill initializes by loading local GTFS static data to resolve station IDs and route names correctly.
- Upon a user request, the agent identifies the relevant transit division such as BDFM or ACE.
- It fetches real-time protobuf or JSON feeds directly from official MTA data service endpoints.
- The raw data is parsed and filtered to match the user's specific station, line, or direction criteria.
- Finally, the skill formats the transit telemetry into a human-readable response featuring arrival times and service status for Openclaw Skills users.
NYC MTA Transit Setup
To integrate this into your Openclaw Skills workflow, follow these steps:
Install Node.js dependencies:
npm install
Refresh the static GTFS data (required on first use to map station IDs):
node scripts/mta.mjs refresh-gtfs
(Optional) For bus data, sign up at the MTA developer portal and set your environment variable:
export MTA_BUS_API_KEY="your_api_key_here"
NYC MTA Transit Data Schema & Taxonomy
The skill manages transit data through a structured local and remote architecture to optimize Openclaw Skills performance:
| Component | Source | Format |
|---|---|---|
| Static GTFS | ~/.mta/gtfs/ |
Local Cached Data |
| Subway Feed | MTA Data Service | GTFS-RT (Protobuf) |
| Bus Feed | BusTime API | SIRI (JSON) |
| Service Alerts | MTA Alerts Feed | GTFS-RT (Protobuf) |
Subway stop IDs are formatted with direction suffixes (N for Northbound, S for Southbound) to ensure precise arrival tracking and clear user communication.
NYC MTA Transit Advanced Features
- Multi-feed subway aggregation automatically fetches data across different line divisions for complex station queries.
- Fuzzy search logic allows users to find stations using natural language names rather than strict MTA IDs.
- Geographic radius searching identifies the closest transit hubs based on latitude and longitude coordinates.
- Real-time vehicle tracking provides the exact GPS coordinates and distance of buses on a given route.
- Integrated service alert filtering provides context-aware warnings for specific lines during planned work or unexpected disruptions.
SKILL.md
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