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LA Metro MCP Server for Cursor 12 tools — connect in under 2 minutes

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Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

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Classic Setup·json
{
  "mcpServers": {
    "la-metro": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
LA Metro
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IAMAccess control
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About LA Metro MCP Server

Connect your LA Metro API Los Angeles public transit data platform to any AI agent and take full control of real-time Metrobus and Metro Rail tracking, arrival predictions, rail-to-rail journey planning, and service disruption monitoring through natural conversation.

Cursor's Agent mode turns LA Metro into an in-editor superpower. Ask Cursor to generate code using live data from LA Metro and it fetches, processes, and writes. all in a single agentic loop. 12 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

What you can do

  • Metrobus Stops — List all bus stops system-wide or filtered by route with coordinates and service messages
  • Metrobus Routes — Browse all Metrobus routes including local, rapid, and express services across LA County
  • Bus Schedules — Get complete schedule data with run patterns and stop sequences for any bus route
  • Bus Vehicle Tracking — Track real-time GPS positions of all active Metrobus vehicles
  • Stop Predictions — Get next bus arrival predictions for any specific bus stop with minutes and seconds
  • Metro Rail Stations — List all rail stations across B (Red), D (Purple), A (Blue), E (Expo), C (Green), and K lines
  • Rail Arrivals — Get next train arrival predictions at any Metro Rail station with line and destination info
  • Rail-to-Rail Planning — Plan rail-only journeys between any two Metro Rail stations with transfer guidance
  • Rail Routes — Browse all Metro Rail lines with colors, station counts, and operational metadata
  • Service Alerts — Monitor active disruptions across Metro Rail and Metrobus with severity and alternatives
  • Rail Vehicle Positions — Track real-time positions of Metro Rail trains across the network
  • Bus Locations — Get real-time bus locations system-wide or filtered by specific route

The LA Metro MCP Server exposes 12 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect LA Metro to Cursor via MCP

Follow these steps to integrate the LA Metro MCP Server with Cursor.

01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

03

Save the file

Cursor will automatically detect the new MCP server

04

Start using LA Metro

Open Agent mode in chat and ask: "Using LA Metro, help me...". 12 tools available

Why Use Cursor with the LA Metro MCP Server

Cursor AI Code Editor provides unique advantages when paired with LA Metro through the Model Context Protocol.

01

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

02

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

03

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

04

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

LA Metro + Cursor Use Cases

Practical scenarios where Cursor combined with the LA Metro MCP Server delivers measurable value.

01

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

02

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

03

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

04

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

LA Metro MCP Tools for Cursor (12)

These 12 tools become available when you connect LA Metro to Cursor via MCP:

01

get_bus_locations

Returns vehicle IDs, route IDs, latitude/longitude coordinates, heading direction, seconds since last report, predictability indicators, and trip/run identifiers. Can query all buses system-wide or filter by specific route ID for targeted route-level tracking. Essential for real-time bus fleet monitoring, passenger arrival estimation, route-level service awareness, and transit operations management. AI agents should reference this when users ask "show me all buses on route 720", "where are the active buses right now", or need real-time bus position data for fleet visualization or arrival prediction. Get real-time bus locations system-wide or for a specific route

02

get_bus_routes

Returns route IDs, route names, types (local, rapid, express, Metro Rail link), direction listings, and route metadata. Covers hundreds of routes serving the entire LA Metro service area including downtown LA, Hollywood, Santa Monica, San Fernando Valley, South Bay, East LA, and beyond. Essential for route discovery, service area analysis, transit network understanding, and identifying route IDs for use in stop and schedule queries. AI agents should reference this when users ask "list all Metrobus routes", "what routes serve downtown LA", or need to identify route IDs for subsequent Metrobus queries. List all Metrobus routes in the LA Metro system

03

get_bus_schedule

Returns run IDs, direction information (inbound/outbound, eastbound/westbound), stop sequences, and scheduled timing data. Essential for schedule analysis, journey planning at specific times, understanding route direction patterns, and passenger trip preparation. AI agents should use this when users ask "show me the schedule for route 720", "what are the run patterns for the 4 line", or need detailed schedule data for a specific bus route to plan trips at specific times. Get the schedule for a specific Metrobus route

04

get_bus_stops

Returns stop IDs, names, geographic coordinates (latitude, longitude), route affiliations, and any service messages or alerts associated with each stop. Essential for stop discovery, journey planning, accessibility mapping, and understanding bus network geography across Los Angeles County. AI agents should use this when users ask "list all stops on the 720 Rapid", "find bus stops near Union Station", or need to identify stop IDs for use in prediction queries. If no route_id is provided, returns all stops system-wide. List all Metrobus stops or stops on a specific bus route

05

get_bus_vehicles

Returns vehicle IDs, route affiliations, latitude/longitude coordinates, heading direction, seconds since last report, predictability indicators (whether the vehicle is running on predicted schedule or actual GPS), and run/trip identifiers. Essential for real-time bus tracking, passenger wait time estimation, bus arrival prediction, and fleet monitoring. AI agents should use this when users ask "where are the buses right now", "track vehicle 1234", or need to locate specific Metrobus vehicles for real-time arrival awareness. Get real-time locations of active Metrobus vehicles

06

get_rail_arrivals

Returns predicted arrival times, train destination names, line colors (Red, Purple, Blue, Expo, Green, Gold, K), direction indicators, and train run identifiers. Essential for real-time rail arrival awareness, passenger waiting time estimation, connection planning, and station-level trip timing. AI agents should reference this when users ask "when is the next Red Line train at Union Station", "show upcoming trains at 7th Street/Metro Center", or need station-specific Metro Rail arrival predictions. Station IDs can be found using get_rail_stations. Get next train arrival predictions at a specific Metro Rail station

07

get_rail_routes

Essential for line identification, rail network understanding, service area analysis, and identifying line IDs for use in rail journey planning. AI agents should reference this when users ask "list all Metro Rail lines", "what lines does Metro operate", or need line metadata for rail network context. List all Metro Rail lines and routes

08

get_rail_stations

Returns station IDs, names, display names, geographic coordinates (latitude, longitude), line affiliations, station order on each line, cross streets, and accessibility information. Essential for station discovery, rail network mapping, route planning, and identifying station IDs for use in arrival and rail-to-rail queries. AI agents should use this when users ask "list all stations on the Red Line", "what is the station code for 7th Street/Metro Center", or need to understand the Metro Rail network geography. List all Metro Rail stations with details

09

get_rail_to_rail

Returns recommended routes, transfer stations, estimated travel times, number of transfers, line sequences, and step-by-step rail directions. Essential for rail trip planning, transfer identification, travel time estimation, and understanding rail connectivity across the Metro network. AI agents should use this when users ask "how do I get from North Hollywood to Santa Monica by rail", "plan a rail trip from Union Station to LAX", or need rail-only journey planning between two Metro Rail stations. Station IDs can be found using get_rail_stations. Get rail-to-rail journey planning between two Metro Rail stations

10

get_rail_vehicle_positions

Returns train identifiers, line affiliations, latitude/longitude coordinates, heading direction, run/trip IDs, and prediction status. Essential for real-time rail tracking, train location awareness, and understanding train distribution across the network. AI agents should use this when users ask "where are the Red Line trains right now", "track train positions on the Expo Line", or need to visualize train locations for operational monitoring or passenger information. Get real-time positions of Metro Rail trains

11

get_service_alerts

Returns alert descriptions, affected routes and stations, severity levels, start and end timestamps, cause types (maintenance, incident, weather, special events), and alternative service recommendations. Essential for service disruption awareness, alternative route planning, passenger communication, and understanding system reliability. AI agents should use this when users ask "are there any delays on the Red Line", "is Metro running normally today", or need to check service reliability before planning Metro journeys. Get current service alerts and disruptions across the LA Metro system

12

get_stop_predictions

Returns predicted arrival times in minutes and seconds, route IDs, run IDs, direction information, departure indicators, and prediction confidence levels. Essential for real-time bus arrival awareness, passenger waiting time estimation, trip timing, and connection coordination. AI agents should reference this when users ask "when is the next bus at stop 5678", "show predictions for this stop", or need real-time arrival data for a specific bus stop. Stop IDs can be found using get_bus_stops. Get next bus arrival predictions for a specific bus stop

Example Prompts for LA Metro in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with LA Metro immediately.

01

"Show me all Metrobus stops on the 720 Rapid route."

02

"What are the next Red Line trains arriving at Union Station?"

03

"Plan a rail journey from North Hollywood to Santa Monica."

Troubleshooting LA Metro MCP Server with Cursor

Common issues when connecting LA Metro to Cursor through the Vinkius, and how to resolve them.

01

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
02

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

LA Metro + Cursor FAQ

Common questions about integrating LA Metro MCP Server with Cursor.

01

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.
02

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.
03

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.
04

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.

Connect LA Metro to Cursor

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.