AeroDataBox MCP for AI. Access global aviation and airport performance stats instantly.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
AeroDataBox provides access to global aviation data through your AI agent. Get real-time flight tracking, current airport departures and arrivals (FIDS), historical delay statistics, and detailed information on aircraft fleets and runway operations.
What AI agents can do with AeroDataBox Automation
Get global delays
Retrieves current global operational delay statistics.
Get alert subscription
Gets specific details about an existing flight alert subscription.
Convert alert subscription
Changes an old style of flight alert subscription to the current credit-based system.
Find out the current location and schedule details for a specific nearby flight number.
Retrieve lists of expected arrivals and departures at an airport, filtering by absolute or relative time frames.
Look up operational performance metrics for airports or global flight paths over specified periods or single dates.
Gather detailed records of flights that have already flown, searchable by callsign, registration, or date.
Access specific operational information like runway configurations and statistical route frequency data for any major airport.
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What AI agents can do with AeroDataBox: 23 Tools
Use these tools to pull everything from current global delay metrics to deep historical flight records in one conversation with your agent.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using AeroDataBox on VinkiusGet Global Delays
Retrieves current global operational delay statistics.
Get Alert Subscription
Gets specific details about an existing flight alert subscription.
Convert Alert Subscription
Changes an old style of flight alert subscription to the current credit-based system.
Create Flight Alert
Sets up a new webhook subscription that triggers when a specific flight event occurs.
Delete Alert Subscription
Removes an existing flight alert webhook subscription entirely.
Get Airline Fleet
Fetches a list of currently active aircraft types used by a specified airline.
Get Airport Delays Historical
Retrieves historical airport delay statistics for an entire day.
Get Airport Delays Period
Gathers historical airport delay data covering a specific date range.
Get Flight History
Searches and returns detailed records of past or scheduled flight movements based on...
Get Global Delays Historical
Retrieves historical data showing global delay patterns over time.
Get Nearest Flight
Provides the current real-time status for a flight that is closest to a specified...
List Alert Subscriptions
Shows all active flight alert webhook subscriptions linked to your account.
Refill Alert Balance
Adds credit balance to the account used for flight alerts.
Get Airport Delays
Checks the current operational delay statistics at a specific airport.
Get Airport Routes Stats
Calculates and returns statistical data on how often certain routes are used at an...
Get Airport Runways
Gets detailed technical specifications and operational details for the runways at a...
Get Airports By Ip
Identifies the closest airports to your current geographical location using an IP...
Get Alert Balance
Checks the remaining credit balance for flight alerts.
Get Distance Time
Calculates the straight-line distance and estimated travel time between two different airports.
Get Fids Absolute
Retrieves a full list of scheduled departures and arrivals at an airport for an...
Get Fids Relative
Gets the schedule board data (FIDS) showing departures and arrivals within a...
Get Flight By Date
Checks the general flight status for a specific date, regardless of current...
Get Flight Delays
Provides historical data on punctuality specifically for one given flight number.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with AeroDataBox, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AeroDataBox. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 23 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Dealing with aviation data used to feel like compiling reports from ten different terminals., Solved with Vinkius AI Gateway
Today, gathering a comprehensive view of air traffic means jumping between an airport's website for FIDS, then logging into a separate historical database to check delays. You copy dates, you switch tabs, and you manually piece together the picture of operational health—a process that eats up hours.
With AeroDataBox, your agent pulls everything in one go. Instead of clicking through multiple dashboards or exporting raw data, you simply ask for a period's worth of delay statistics, and you get the structured, analyzed result instantly.
AeroDataBox: Global Aviation Data At Your Fingertips
The most tedious parts vanish. You never have to manually query run-by-run flight movements or calculate distance and time between two points again. The agent handles the complex parameters for get_airport_routes_stats, giving you immediate insight into route popularity.
Now, instead of spending half a day gathering evidence, you spend that time acting on it. It's that simple.
What your AI can actually do with this
Use this MCP to pull massive amounts of global aviation data using natural language instructions. You can ask your agent for the nearest flight status or check what's happening at a major hub right now, pulling current arrivals and departures. Need to analyze how bad the delays were last month? You can look up historical airport performance across specific date ranges or even compare delay statistics year over year.
It handles everything from simple real-time queries to complex statistical deep dives on things like route frequencies or aircraft types. Connecting this via Vinkius means you get immediate access to this entire dataset, letting your agent handle the heavy lifting so you don't have to manually export spreadsheets.
019ea5df-79ec-7232-a625-143b927311bc Here's how it actually works
The bottom line is that your agent handles complex API calls, so you just talk about flights and get accurate data back.
Subscribe to this MCP and input your unique AeroDataBox API key.
Tell your AI client exactly what aviation data you need, like 'Show me all departures at JFK in the next three hours.'
The agent calls the necessary tool, retrieves the structured flight information, and presents it directly to you.
Who is this actually for?
Aviation Operations Managers who spend too much time switching between different tracking websites. Data Analysts needing reliable historical flight records for compliance or trend modeling. Logistics Planners whose job depends on knowing the current status of multiple interconnected flights.
Uses this MCP to check current airport delays and runway data to quickly reroute ground crews during a disruption.
Runs historical flight movements reports, checking if certain routes are consistently late or if specific aircraft types are underperforming.
Gathers time-series airport delay data across multiple years for quarterly performance reporting without manual API scripting.
What Changes When You Connect
Stop checking multiple websites for delays. Use get_airport_delays to pull current operational status at any major hub directly into your agent's response.
Need flight schedules? Instead of browsing an airport website, use get_fids_relative or get_fids_absolute to pull precise departure and arrival lists for a specific time window.
Analyzing performance doesn't mean manual exports. Run historical reports using get_airport_delays_period or get_global_delays_historical to build trend data instantly.
Go beyond simple tracking. Use get_airport_routes_stats or get_airline_fleet to understand the underlying operational capacity and types of traffic an airport handles.
It saves time on routine checks. Use get_nearest_flight to check status without knowing the exact coordinates, just by providing a flight number.
See it in action
Airlines needing rapid incident response
An agent detects an unusual cluster of late flights. The user asks it to 'What were the average delays at LAX over the last two weeks?' The agent uses get_airport_delays_period and presents a summary, allowing the ops team to immediately identify systemic issues.
Travel agents planning complex itineraries
The user asks for travel options between three cities. The agent first calls get_distance_time to calculate optimal travel windows, then uses get_nearest_flight to verify the current status of connecting legs.
Developers building smart airport assistants
The system needs a daily dashboard update. It automatically triggers a call to get_fids_relative for the next 4 hours at the local hub, ensuring the information is fresh and ready when staff arrive.
Financial analysts tracking economic activity
The analyst needs proof of traffic volume. They ask the agent to compile all historical flight movements (using get_flight_history) for a specific month, providing data points for market analysis.
The honest tradeoffs
Trying to find real-time status via history
Asking the agent 'What was the delay at JFK yesterday?' The agent cannot fulfill this request because historical data tools are for trends, not specific moment reports.
For current operational delays, use get_airport_delays. For past performance patterns, use get_airport_delays_historical and specify a date.
Assuming all airports are tracked equally
Asking for detailed runway data on an airport that isn't in the system's coverage area.
Before querying physical details, use get_airports_by_ip to confirm the closest viable airport codes. Then, you can use get_airport_runways.
Asking for future status without a period
Prompting 'What will happen next week at MIA?' The agent won't know because it needs defined time windows.
Use the get_fids_absolute tool, specifying the start and end date/time range you want to check.
When It Fits, When It Doesn't
Use this MCP if your workflow requires synthesizing aviation data from multiple sources—from real-time tracking (like using get_nearest_flight) to long-term statistical analysis (using get_global_delays_historical). It's ideal for roles that monitor systemic performance or build complex scheduling tools. Don't use it just because you need a single piece of data, like checking one flight number; while you can do that, dedicated simple tracking APIs might be faster.
If your only goal is to check the status of a handful of flights right now and you don't care about history or airport capacity, you might use a simpler, focused API. But if you need to build an assistant that answers questions like 'What is the average delay rate for this hub compared to last quarter?' then AeroDataBox is exactly what you need.
Questions you might have
Can AeroDataBox give me the real-time status of a flight using get_nearest_flight? +
Yes, get_nearest_flight checks the current operational status for any nearby flight number. It provides the up-to-the-minute details on departure and arrival times.
How do I check historical airport delays with AeroDataBox? +
You use get_airport_delays_historical or get_airport_delays_period. These tools let you pull performance data for a full day or an entire range of days.
What is the difference between get_fids_absolute and get_fids_relative? +
get_fids_absolute requires you to provide exact start and end times, while get_fids_relative lets you check departures and arrivals within a timeframe like 'the next four hours'.
How can I find out what aircraft an airline operates? +
You use the get_airline_fleet tool. Just provide the airline's name, and it returns a list of currently active aircraft types they run.
Does AeroDataBox help me plan routes between airports? +
Yes, you can use get_distance_time to calculate both the physical distance and the estimated travel time connecting any two major airports.
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