FlightAware MCP Server for Cursor 12 tools — connect in under 2 minutes
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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{
"mcpServers": {
"flightaware": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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 FlightAware MCP Server
Connect your FlightAware AeroAPI aviation data platform to any AI agent and take full control of global flight tracking, airport operations monitoring, and historical flight analysis through natural conversation.
Cursor's Agent mode turns FlightAware into an in-editor superpower. Ask Cursor to generate code using live data from FlightAware 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
- Flight Search — Find active and recent flights by flight number, tail number, or origin-destination pair
- Flight Status — Get complete status details including gates, runways, scheduled vs. actual times, and delay indicators
- Route Tracking — Access filed flight plans with all waypoints, airways, and altitude restrictions
- Flight Maps — Retrieve static map images showing complete flight tracks from departure to arrival
- Airport Intelligence — Query airport static data, arrivals, departures, and real-time weather observations
- Airline Operations — Monitor entire airline fleets with all active flights by operator/airline code
- Aircraft Registry — Look up aircraft specifications, ownership, registration status, and equipment type
- Historical Analysis — Access flight history dating back to 2011 with complete track points and performance data
- Route Planning — Discover commonly filed routes between any two airports for flight planning and research
- Weather Impact — Check METAR/TAF weather data to assess meteorological impact on flight operations
The FlightAware 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 FlightAware to Cursor via MCP
Follow these steps to integrate the FlightAware MCP Server with Cursor.
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
Save the file
Cursor will automatically detect the new MCP server
Start using FlightAware
Open Agent mode in chat and ask: "Using FlightAware, help me...". 12 tools available
Why Use Cursor with the FlightAware MCP Server
Cursor AI Code Editor provides unique advantages when paired with FlightAware through the Model Context Protocol.
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
FlightAware + Cursor Use Cases
Practical scenarios where Cursor combined with the FlightAware MCP Server delivers measurable value.
Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP
Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically
Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates
Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data
FlightAware MCP Tools for Cursor (12)
These 12 tools become available when you connect FlightAware to Cursor via MCP:
get_aircraft_info
g., "N12345" for US-registered, "G-EUUU" for UK). Returns aircraft type (manufacturer and model), registration country, owner/operator information, registration status, year built, engine type (jet, turboprop, piston), number of engines, and category (airline, business jet, private, cargo, military). Critical for aviation enthusiasts, fleet tracking, aircraft utilization analysis, and private aviation monitoring. AI agents should reference this when users ask "tell me about aircraft N12345", "who owns this tail number", or need aircraft specifications to contextualize flight data. Get registration details and specifications for a specific aircraft
get_airport_arrivals
Returns a list of inbound flights with airline/operator, flight number, aircraft type, origin airport, scheduled and estimated/actual arrival times, arrival runway and gate, and current flight status (en-route, landed, delayed, cancelled, diverted). Essential for airport operations management, passenger pickup coordination, ground handling planning, and arrival delay monitoring. AI agents should reference this when users ask "what flights are arriving at X", "show me arrivals at Y airport", or need to track inbound flights for a specific destination. List arriving flights at a specific airport
get_airport_departures
Returns a list of outbound flights with airline/operator, flight number, aircraft type, destination airport, scheduled and estimated/actual departure times, departure runway and gate, and current flight status (scheduled, boarding, departed, delayed, cancelled, diverted). Critical for airport operations coordination, passenger departure monitoring, gate management, and departure delay tracking. AI agents use this when users ask "what flights are leaving from X", "show me departures at Y airport", or need to track outbound flights from a specific origin. List departing flights from a specific airport
get_airport_info
g., "KJFK" for New York JFK, "KLAX" for Los Angeles International). Returns airport name, location (city, state, country), ICAO/IATA/FAA/LID codes, geographic coordinates (latitude, longitude, elevation), timezone, runway information, and canonical FlightAware ID. Essential for airport identification, travel planning, flight briefing preparation, and geographic reference. AI agents should use this when users ask "tell me about airport X", "what is the ICAO code for Y", or need airport metadata to contextualize flight queries. Get static information and details for a specific airport
get_airport_routes
Returns route strings, frequency of use, typical altitudes, and associated flight examples. Essential for flight planning, route optimization analysis, aviation research, and pilot briefing preparation. AI agents should reference this when users ask "what routes are flown between X and Y", "show me common paths from JFK to LAX", or need to understand routing options between airport pairs for planning or analysis purposes. Get routes between two specific airports
get_airport_weather
Returns METAR (avi routine weather report) data including wind speed and direction, visibility, cloud layers, temperature, dewpoint, altimeter setting, present weather phenomena (rain, snow, fog, thunderstorms), and automated weather remarks. Also provides TAF (terminal aerodrome forecast) for upcoming weather conditions. Essential for flight planning, aviation safety assessment, delay prediction due to weather, and pilot briefing preparation. AI agents should query this when users ask "what is the weather at X airport", "is weather affecting flights at Y", or need to assess meteorological impact on flight operations. Get current weather observations and forecast for a specific airport
get_flight_map
The map shows the filed route, actual track points, departure and arrival airports, and current aircraft position (if airborne). Useful for visual flight presentation, passenger communication, operations dashboards, and flight tracking displays. AI agents should reference this when users request to "show me the flight path" or "where is this flight on a map". Returns image URL that can be embedded in responses or displayed directly. Get a static map image showing the flight track
get_flight_route
Returns the route as a structured list of fixes, navaids, and airway segments from departure to arrival airport. Essential for flight following, aviation enthusiast tracking, pilot briefing preparation, and route analysis. AI agents use this to visualize flight paths, compare filed routes against actual tracks, analyze common routing patterns between airport pairs, and provide pilots with route reference data. Get the filed flight plan route for a specific flight
get_flight_status
Returns departure and arrival airports with terminals and gates, scheduled/estimated/actual times for pushback, takeoff, landing, and arrival, current flight status (en-route, landed, diverted, cancelled, in-hold), delay indicators, aircraft registration and type, route description, and diversion airports if applicable. Critical for passenger travel updates, airline operations coordination, and flight tracking dashboards. AI agents should reference this when users request detailed status for a known flight ID, including gate assignments, delay reasons, and actual vs. scheduled time comparisons. Get complete status details for a specific flight
get_historical_flights
Access continuous flight history data dating back to January 1, 2011, including actual departure and arrival times, route flown, all track points (latitude, longitude, altitude, ground speed, timestamp), arrival status, and delay indicators. Essential for post-flight analysis, operational trend identification, schedule reliability assessment, on-time performance tracking, and aviation safety investigations. AI agents use this when users ask "show me the history of flight X", "how has this route performed over time", or need to analyze historical flight patterns for reliability studies. Get historical flight data and track for a specific flight
get_operator_flights
g., "UAL" for United Airlines, "DAL" for Delta, "BAW" for British Airways). Returns flight numbers, aircraft types, origin-destination pairs, scheduled and actual times, and current status for all flights in the operator fleet. Essential for airline operations monitoring, fleet utilization analysis, competitor intelligence, and passenger rebooking during disruptions. AI agents use this when users ask "show me all United flights", "what is Delta flying right now", or need to track an entire airline operational picture. List all flights operated by a specific airline or operator
search_flights
The query can be a flight number (e.g., "UAL123"), aircraft tail number/registration (e.g., "N12345"), or origin-destination pair (e.g., "KJFK-KLAX"). Returns complete flight identification, airline/operator, aircraft type, departure and arrival airports, scheduled and actual times, current position (if airborne), altitude, ground speed, and flight status (en-route, landed, diverted, cancelled). Essential for real-time flight tracking, passenger pick-up coordination, logistics planning, and aviation operations monitoring. AI agents should use this when users ask "where is flight X", "what flights are flying from A to B", or "show me all flights by tail number N". Search for active and recent flights by flight number, tail number, or route
Example Prompts for FlightAware in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with FlightAware immediately.
"Search for all active United Airlines flights from Newark (KEWR) to San Francisco (KSFO)."
"What is the current weather at Chicago O'Hare (KORD) and are flights being delayed due to conditions?"
"Show me the complete flight history and track points for British Airways flight BAW117 from London to New York yesterday."
Troubleshooting FlightAware MCP Server with Cursor
Common issues when connecting FlightAware to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
FlightAware + Cursor FAQ
Common questions about integrating FlightAware MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
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?
How do I verify MCP tools are loaded?
Connect FlightAware with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect FlightAware to Cursor
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.