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MTA MCP Server for Cline 12 tools — connect in under 2 minutes

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Cline is an autonomous AI coding agent inside VS Code that plans, executes, and iterates on tasks. Wire MTA through Vinkius and Cline gains direct access to every tool. from data retrieval to workflow automation. without leaving the terminal.

Vinkius supports streamable HTTP and SSE.

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Classic Setup·json
{
  "mcpServers": {
    "mta": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
MTA
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IAMAccess control
EU AI ActCompliant
DLPData protection
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<40msKill switch
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 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.

Cline operates autonomously inside VS Code. it reads your codebase, plans a strategy, and executes multi-step tasks including MTA tool calls without waiting for prompts between steps. Connect 12 tools through Vinkius and Cline can fetch data, generate code, and commit changes in a single autonomous run.

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

The MTA MCP Server exposes 12 tools through the Vinkius. Connect it to Cline 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 MTA to Cline via MCP

Follow these steps to integrate the MTA MCP Server with Cline.

01

Open Cline MCP Settings

Click the MCP Servers icon in the Cline sidebar panel

02

Add remote server

Click "Add MCP Server" and paste the configuration above

03

Enable the server

Toggle the server switch to ON

04

Start using MTA

Ask Cline: "Using MTA, help me...". 12 tools available

Why Use Cline with the MTA MCP Server

Cline provides unique advantages when paired with MTA through the Model Context Protocol.

01

Cline operates autonomously. it reads your codebase, plans a strategy, and executes multi-step tasks including MCP tool calls without step-by-step prompts

02

Runs inside VS Code, so you get MCP tool access alongside your existing extensions, terminal, and version control in a single window

03

Cline can create, edit, and delete files based on MCP tool responses, enabling end-to-end automation from data retrieval to code generation

04

Transparent execution: every tool call and file change is shown in Cline's activity log for full visibility and approval before committing

MTA + Cline Use Cases

Practical scenarios where Cline combined with the MTA MCP Server delivers measurable value.

01

Autonomous feature building: tell Cline to fetch data from MTA and scaffold a complete module with types, handlers, and tests

02

Codebase refactoring: use MTA tools to validate live data while Cline restructures your code to match updated schemas

03

Automated testing: Cline fetches real responses from MTA and generates snapshot tests or mocks based on actual payloads

04

Incident response: query MTA for real-time status and let Cline generate hotfix patches based on the findings

MTA MCP Tools for Cline (12)

These 12 tools become available when you connect MTA to Cline via MCP:

01

get_bus_estimated_arrival

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

02

get_bus_predictions

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

03

get_bus_routes

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

04

get_bus_stops

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

05

get_bus_vehicle_at_stop

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

06

get_bus_vehicles

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

07

get_lirr_feed

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

08

get_metro_north_feed

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

09

get_service_alerts

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

10

get_stations

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

11

get_subway_feed

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

12

get_system_time

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

Example Prompts for MTA in Cline

Ready-to-use prompts you can give your Cline agent to start working with MTA immediately.

01

"Show me the next trains on the 1/2/3 line."

02

"When is the next M15 bus arriving at the stop near 14th Street and 3rd Avenue?"

03

"Check if there are any service alerts affecting the LIRR right now."

Troubleshooting MTA MCP Server with Cline

Common issues when connecting MTA to Cline through the Vinkius, and how to resolve them.

01

Server shows error in sidebar

Click the server name to see logs. Verify the URL and token are correct.

MTA + Cline FAQ

Common questions about integrating MTA MCP Server with Cline.

01

How does Cline connect to MCP servers?

Cline reads MCP server configurations from its settings panel in VS Code. Add the server URL and Cline discovers all available tools on initialization.
02

Can Cline run MCP tools without approval?

By default, Cline asks for confirmation before executing tool calls. You can configure auto-approval rules for trusted servers in the settings.
03

Does Cline support multiple MCP servers at once?

Yes. Configure as many servers as needed. Cline can use tools from different servers within the same autonomous task execution.

Connect MTA to Cline

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