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How to Use the WMATA MCP in CrewAI

Run autonomous WMATA operations using CrewAI's specialized multi-agent collaboration framework.

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CrewAI

Connect WMATA MCP to CrewAI

Create your Vinkius account to connect WMATA to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Autonomous Network Analysis

Define a Research Agent that runs `get_bus_routes` to list all available routes. Then, pass these IDs to an Analysis Agent which uses `get_bus_route_details` to map out every stop and sequence for journey planning. The CrewAI framework makes this collaboration possible: specialized agents handle the data retrieval and structuring automatically.

Real-Time Coordination Monitoring

Build a monitoring crew that simultaneously checks two sources. One agent runs `get_next_rail` for system-wide train predictions, while another runs `get_circuit_predictions` for bus arrivals at Union Station. The moderator agent then synthesizes the combined schedule into one report. This allows autonomous coordination between Metrorail and Metrobus services.

Comprehensive Service Verification

A specialized Agent can run a check combining `get_rail_incidents` (Metrorail) with `get_bus_incidents` (Metrobus). If both tools report active incidents, the action agent compiles a full status update detailing impacts, severities, and necessary detours. This comprehensive service verification is crucial for emergency or high-stakes operational reports.

Setup guide

Set up WMATA MCP in CrewAI

Prerequisites

  • Python 3.10+ installed
  • crewai package (pip install crewai)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install CrewAI

    Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.

  2. 2

    Add the MCP URL to your agent

    Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.

  3. 3

    Kick off your crew

    Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke WMATA tools as needed.

crew.py
from crewai import Agent, Task, Crew

agent = Agent(
    role="WMATA Analyst",
    goal="Access and analyze WMATA data via MCP.",
    backstory="Expert analyst with direct WMATA access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent WMATA transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Common questions about WMATA MCP in CrewAI

You use `get_elevator_incidents` to get outage details. A dedicated agent checks the affected station codes and compares them against the full list of stations provided by another agent calling `get_rail_stations`.
One agent calls `get_parking_lots` to check lot capacity. A second agent uses `get_station_entrances` on that station code to confirm street access and entry points.
The server touches network structure via `get_bus_route_details`, which lists all stops served by a route, providing detailed service area coverage maps.
Yes. The agent needs the station code (e.g., 'A01') to pass into `get_station_prediction`. It's essential that another step in the crew calls `get_rail_stations` first.
Run `get_bus_route_details` using the desired route ID. This returns all stops served by that specific Metrobus line, giving you the full sequence and coverage details.

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