Bring Real Time Transit
to Cursor
Create your Vinkius account to connect MTA to Cursor and start using all 12 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
Compatible with every major AI agent and IDE
What is the MTA MCP Server?
Connect your MTA API New York City public transit data platform to any AI agent and take full control of real-time NYC Subway and MTA Bus tracking, arrival predictions, LIRR and Metro-North commuter rail monitoring, and service disruption awareness through natural conversation.
What you can do
- Subway Real-Time Feeds — Access live GTFS-RT data for all NYC Subway lines with train positions and arrival predictions
- Bus Routes — List all MTA bus routes across Manhattan, Brooklyn, Queens, Bronx, and Staten Island
- Bus Stops — Get all stops for any bus route with coordinates and sequence information
- Bus Predictions — Get real-time estimated arrival times for any bus stop
- Bus Vehicle Tracking — Track real-time GPS positions of all active MTA bus vehicles
- Service Alerts — Monitor active disruptions across Subway, buses, LIRR, and Metro-North
- Subway Stations — List all 472 NYC Subway stations with coordinates, borough, and entrance data
- LIRR Tracking — Monitor Long Island Rail Road trains with real-time positions and arrivals
- Metro-North Tracking — Track Metro-North Railroad trains serving northern NYC suburbs
- Stop-Level Bus Monitoring — Monitor buses at specific stops with targeted arrival predictions
- Estimated Arrivals — Get route-filtered arrival estimates for buses at any stop
- System Connectivity — Verify API connectivity and synchronize timestamps
How it works
- Subscribe to this server
- Enter your MTA API key (free from the Developer Portal)
- Start tracking NYC transit from Claude, Cursor, or any MCP-compatible client
No more navigating multiple MTA apps or manually checking train and bus times. Your AI acts as a dedicated NYC transit analyst and trip planning assistant.
Who is this for?
- NYC Commuters — track subway and buses, check arrivals, and monitor LIRR/Metro-North for daily commutes
- Tourists — navigate the NYC Subway system with station discovery and real-time arrival awareness
- Transit Analysts — research service patterns, vehicle positions, and system reliability across all MTA modes
- Mobility Apps — integrate real-time MTA data into journey planning and transit tracking applications
Built-in capabilities (12)
Returns predicted arrival times, route information, destinations, wait times, and delay indicators for each expected bus. Supports both multi-route stop queries and single-route filtered queries. Essential for targeted arrival predictions, route-specific wait time estimation, and passenger trip timing. AI agents should reference this when users ask "when is the next M15 at this stop", "show arrival estimates for route B46 at stop 12345", or need route-filtered arrival data at a specific bus stop. Get estimated arrival times for buses at a stop, optionally filtered by route
Returns predicted arrival times, route IDs, destination information, expected wait times, and whether buses are on schedule or delayed. Based on real-time vehicle tracking and schedule adherence. 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 M15 bus at stop 12345", "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
Returns route IDs, route names, operators (MTA New York City Bus, MTA Bus Company, private operators under MTA contract), and service area information. Covers local, limited-stop, and Select Bus Service (SBS) routes. Essential for route discovery, service area analysis, transit network understanding, and identifying route IDs for use in stop and prediction queries. AI agents should reference this when users ask "list all bus routes in Manhattan", "what routes serve Brooklyn", or need to identify route IDs for subsequent MTA Bus Time queries. List all MTA bus routes in New York City
Returns stop IDs (MonitoringRef), stop names, geographic coordinates (latitude, longitude), stop sequence order, and direction information. Essential for stop discovery, journey planning, accessibility mapping, and identifying stop IDs for use in arrival prediction queries. AI agents should use this when users ask "list all stops on the M15", "find bus stops along Broadway", or need to identify stop IDs for use in get_bus_predictions queries. List all stops for a specific MTA bus route
Returns vehicle IDs, route IDs, current positions, expected arrival times, distances from stop, and operational status. More targeted than system-wide vehicle queries. Essential for stop-level bus tracking, passenger waiting awareness, and real-time arrival estimation at specific stops. AI agents should use this when users ask "what buses are coming to this stop", "track vehicles approaching stop 12345", or need stop-specific bus position data for passenger information. Get buses currently at or approaching a specific bus stop
Returns vehicle IDs, route affiliations, latitude/longitude coordinates, heading direction, speed, recorded time, and prediction availability. Covers all MTA New York City Bus and MTA Bus Company vehicles in active service. Essential for real-time bus fleet monitoring, passenger arrival estimation, route-level service awareness, and transit operations management. AI agents should use this when users ask "where are all the buses right now", "track bus positions system-wide", or need real-time vehicle position data for fleet visualization. Get real-time positions of all active MTA bus vehicles
Returns train positions, trip updates, scheduled vs. real-time arrivals at stations, delays, track information, and service disruptions across all LIRR branches including Babylon, Ronkonkoma, Hempstead, Port Jefferson, Montauk, and more. Essential for commuter rail tracking, arrival predictions at Penn Station and Grand Central Madison, and LIRR service monitoring. AI agents should reference this when users ask "when is the next LIRR train to Penn Station", "track LIRR train positions", or need real-time commuter rail data for trip planning from Long Island into NYC. Get real-time LIRR train data from the Long Island Rail Road
Returns train positions, trip updates, scheduled vs. real-time arrivals, delays, track information, and service disruptions across all Metro-North lines including Hudson, Harlem, New Haven, Port Jervis, Pascack Valley, and more. Essential for commuter rail tracking, arrival predictions at Grand Central Madison, and Metro-North service monitoring. AI agents should use this when users ask "when is the next Metro-North train from White Plains", "track Metro-North positions", or need real-time commuter rail data for trip planning from Westchester, Connecticut, or the Hudson Valley into NYC. Get real-time Metro-North Railroad train data
Returns alert descriptions, affected lines and stations, severity levels, cause types (maintenance, incident, weather, special events, construction), start and end timestamps, 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 4/5/6 line", "is LIRR running normally", or need to check service reliability before planning MTA journeys. Get current service alerts and disruptions across the MTA system
Returns station IDs, station names, complex IDs (for multi-line stations), borough information (Manhattan, Brooklyn, Queens, Bronx, Staten Island), structure types (underground, elevated, embankment, open cut), latitude/longitude coordinates, and North/East/South/West entrance coordinates. Essential for station discovery, rail network mapping, route planning, and identifying station codes for use in journey planning queries. AI agents should use this when users ask "list all stations in Manhattan", "what is the station code for Times Square", or need to understand the NYC Subway network geography. List all NYC Subway stations with details
Supports feed IDs grouped by line: "1" (lines 1,2,3,4,5,6,S), "2" (lines A,C,E), "3" (lines B,D,F,M), "4" (lines G), "5" (lines J,Z), "6" (lines N,Q,R,W), "7" (lines L), "11" (Staten Island Railway), "16" (Shuttle 42nd St), "21" (Shuttle Franklin Ave), "26" (Shuttle Rockaway Park). Returns train positions, trip updates, scheduled vs. real-time arrivals, delays, and service disruptions. Essential for real-time subway tracking, arrival predictions, and service monitoring across the entire NYC Subway system. AI agents should use this when users ask "when is the next 1 train", "show real-time positions for the A line", or need live subway data for trip planning. Feed IDs are required and can be found in MTA documentation. Get real-time subway feed data for specific NYC Subway lines
Returns the official server timestamp in ISO 8601 format. Useful for synchronizing local clocks with the MTA system, verifying API connectivity, testing authentication, and timestamp alignment for real-time data correlation. AI agents should use this as a connectivity check before making more complex queries, or when users need to verify API responsiveness and authentication validity. Get the current MTA Bus Time system timestamp
Why Cursor?
Cursor's Agent mode turns MTA into an in-editor superpower. Ask Cursor to generate code using live data from MTA 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.
- —
Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
- —
Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
- —
MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
- —
VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
MTA in Cursor
Why run MTA with Vinkius?
The MTA connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 12 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.

* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.




Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect MTA using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
MTA and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect MTA to Cursor through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
MTA for Cursor
Every request between Cursor and MTA is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
Can my AI check when the next subway train is arriving at my station?
Yes! Use the get_subway_feed tool with the appropriate feed ID for your line. Feed IDs are grouped: "1" covers lines 1,2,3,4,5,6,S; "2" covers A,C,E; "3" covers B,D,F,M; "4" is G; "5" is J,Z; "6" covers N,Q,R,W; "7" is L; "11" is Staten Island Railway. This returns real-time GTFS-RT data with train positions, trip updates, scheduled vs. real-time arrivals, and delay information. For station-level predictions, combine with get_stations to find your station code first.
How do I check when the next MTA bus is arriving at a specific stop?
First use get_bus_stops with a route ID to find the stop ID (MonitoringRef) for your location. Then use get_bus_predictions with that stop ID to get real-time estimated arrival times, route information, destinations, and delay indicators. For more targeted predictions, use get_bus_estimated_arrival which allows filtering by both stop ID and route ID. Stop IDs are numeric identifiers assigned by MTA to each physical bus stop across NYC.
Are there any service disruptions affecting my subway line or bus route right now?
Use get_service_alerts to check all active service disruptions across the MTA system. This returns alerts with affected lines and stations, disruption descriptions, severity levels, cause types (maintenance, incident, weather, special events, construction), start and end timestamps, and alternative service recommendations. Covers NYC Subway, buses, LIRR, and Metro-North. Always check this before planning any journey to ensure you are aware of delays, planned work, 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.
Explore More MCP Servers
View all →
Erply ERP & POS
10 toolsEquip your AI agent to manage retail products, track sales invoices, and monitor inventory via the Erply API.

SendGrid Email Sender
1 toolsThis MCP does exactly one thing: it sends transactional emails using Twilio SendGrid. That's its only function, and nothing else. Incredible for giving your AI agents the ability to dispatch email reports.

Exact Online Bouw
12 toolsManage Dutch construction accounting with project budgets, cost tracking, and financial reporting built for the building industry.

Telegram Bot Alternative
12 toolsControl and manage your Telegram bots — send messages, photos, and audit chats via AI.
