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mbta

Real-time MBTA transit predictions for Boston-area subway, bus, commuter rail, and ferry. Query departure times, search stops/routes, check service alerts, and run a live dashboard. Use when asked about Boston transit, T schedules, when to leave for the train, or MBTA service status.

Why use this skill?

Get real-time MBTA train and bus predictions, check service alerts, and track your Boston commute with the OpenClaw MBTA transit skill. Easy setup for local riders.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/dbhurley/mbta
Or

What This Skill Does

The MBTA Transit skill provides OpenClaw users with real-time access to the Massachusetts Bay Transportation Authority (MBTA) v3 API. This powerful utility allows you to fetch live departure predictions, check service status updates, and view schedules for all subway lines, buses, commuter rail, and ferry services in the Greater Boston area. By integrating directly with MBTA data, the agent can help you plan your commute, avoid service disruptions, and decide exactly when you need to leave your house to catch your train or bus.

Installation

To install this skill, run the following command in your terminal: clawhub install openclaw/skills/skills/dbhurley/mbta

Ensure you have Python installed and run pip install requests pyyaml flask. While not strictly required, obtaining a free API key from the MBTA API portal is highly recommended to avoid rate limits during high-traffic periods. Once installed, define your personal commute in the config.yaml file to enable the intelligent departure dashboard.

Use Cases

This skill is perfect for daily commuters or visitors to Boston. Common use cases include:

  • Commute Planning: Querying next departures for specific stops to manage your morning routine.
  • Service Monitoring: Checking for active service alerts or delays on specific routes before you leave your home.
  • Dashboarding: Running a live, persistent web dashboard that shows departures specifically filtered by your walking time to the station.
  • Route Discovery: Identifying the correct stop IDs or route IDs for your specific transit needs.

Example Prompts

  1. "When is the next Red Line train leaving from Harvard Square?"
  2. "Are there any delays currently affecting the Orange Line?"
  3. "Should I leave now to make it to the South Station commuter rail on time?"

Tips & Limitations

  • Configuration: Always set your walk_minutes in config.yaml to match your actual travel time to the station. The agent uses this to filter out trains you cannot realistically catch.
  • Data Accuracy: Predictions are real-time, but transit conditions can change instantly. Always treat times as estimates.
  • Stop IDs: Use the python scripts/mbta.py stops --search "name" command if you are unsure of the correct ID for your local station.
  • Machine-Readable Format: If you are building automated pipelines or custom UIs, remember to append the --json flag to your command line queries for standardized output.

Metadata

Author@dbhurley
Stars1100
Views1
Updated2026-02-17
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-dbhurley-mbta": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#boston#transit#mbta#commute#realtime
Safety Score: 5/5

Flags: network-access, file-read, external-api