Bring Public Transit
to Cursor
Learn how to connect LA Metro to Cursor and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the 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.
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
How it works
1. Subscribe to this server
2. Enter your LA Metro API key (if required — many endpoints are open data)
3. Start tracking LA Metro transit from Claude, Cursor, or any MCP-compatible client
No more navigating the Metro website or manually checking train and bus times. Your AI acts as a dedicated LA transit analyst and trip planning assistant.
Who is this for?
- LA Commuters — track buses and rail, check arrivals, and plan rail-only trips across LA County
- Tourists — navigate the Metro Rail system with station discovery and rail-to-rail journey planning
- Transit Analysts — research service patterns, vehicle positions, and system reliability
- Mobility Apps — integrate real-time LA Metro data into journey planning and transit tracking applications
Built-in capabilities (12)
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
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
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
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
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
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
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
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
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
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
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
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
Why Cursor?
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.
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Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
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Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
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MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
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VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
LA Metro in Cursor
LA Metro and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect LA Metro to Cursor through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LA Metro in Cursor
The LA Metro 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Cursor only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
LA Metro for Cursor
Every tool call from Cursor to the LA Metro MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can my AI check when the next Metrobus is arriving at a specific stop in LA?
Yes! First use get_bus_stops with a route_id to find the stop ID for your location. Then use get_stop_predictions with that stop ID to get real-time arrival predictions in minutes and seconds, including route numbers, direction, and whether the bus is departing soon. This gives you live predictions based on actual vehicle GPS positions and schedule adherence.
How do I plan a Metro Rail journey from one station to another?
Use get_rail_stations first to find the station IDs for your origin and destination. Then use get_rail_to_rail with both station IDs to get the recommended rail route with transfer stations, estimated travel time, number of transfers, and step-by-step directions. You can also use get_rail_arrivals at your origin station to see when the next trains are coming.
Are there any service disruptions affecting Metro Rail or Metrobus right now?
Use get_service_alerts to check all active service disruptions across the LA Metro system. This returns alerts with affected routes and stations, disruption descriptions, severity levels, cause types (maintenance, incident, weather, special events), start and end times, and alternative service recommendations. Check this before planning any journey to ensure you are aware of delays or service changes.
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.
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.
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.
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.
Tools not appearing in Cursor
Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
Server shows as disconnected
Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.
