SkyLinkAPI MCP Server | Aviation Data MCP Server

Connect SkyLink API to Claude Desktop, Cursor, or any MCP client in under a minute. Ask about live flights, weather, NOTAMs, and ADS-B positions — your AI gets real data, not hallucinations.

Plug live SkyLink aviation data straight into Claude, Cursor, or any MCP-compatible client - every endpoint becomes a tool the model can call, with no glue code and no scraping.

One config block connects your MCP client to SkyLink - then the model can pull weather, airports, ADS-B, charts, and more, just by asking.

Add one server block - works with any MCP-compatible client.

The model picks the right tool and calls it for you.

The whole API, as callable tools. A sample of what the model can reach.

weather.metarairports.searchadsb.aircraftflight_statuschartscarbon.estimateml.flight_timenotamshistory.flights

Add your API key to the config and your AI is connected - works on the free tier.

A hosted bridge between your AI client and the full SkyLink v3.1 API - no servers to run, no integration code to write.

Claude Desktop, Cursor, Cline, Windsurf, or anything that speaks the Model Context Protocol - paste one config block and you're connected.

Weather, airports, ADS-B, charts, flight status, carbon, ML estimates - the whole v3.1 surface is exposed as tools the model can invoke.

No SDK wiring, no request plumbing, no response parsing. The MCP layer handles tool schemas and calls - you just describe what you want.

The server is a streamable HTTP endpoint we run - no self-hosting, no bridge process, no infrastructure to maintain. Point your client at the URL and go.

Ask in plain English - the model chooses the right endpoint, fills in the parameters, and grounds its answer in live SkyLink data.

Your API key lives in the client's config header - sent as a transport header, never embedded in prompts or exposed to the model.

Paste one block into your MCP client's config, swap in your API key, and restart. The server is a hosted HTTP endpoint - nothing to run yourself.

{ "mcpServers": { "skylink": { "url": "https://data.skylinkapi.com/mcp", "headers": { "x-api-key": "YOUR_API_KEY" } } } }

ReplaceYOUR_API_KEY· no self-hosting required
- 1Settings → Developer → Edit Config
- 2Paste intomcpServers
- 3Restart Claude Desktop
- 1Settings → MCP
- 2Add MCP Server
- 3Paste the config block

Once connected, your AI reaches for SkyLink tools on its own - picking the right endpoint, filling in parameters, and grounding its answer in live data.

No prompt engineering for API calls, no copy-pasting JSON. Just a question and a grounded answer.

Claude · SkyLink MCP connectedLive tools

Is EGLL good for a CAT III approach right now, and what's the great-circle distance to KJFK?

weather.metar(EGLL)notams(EGLL)distance(EGLL, KJFK)

EGLL is reporting 200 m RVR in fog - within CAT III minima, but one NOTAM has ILS CAT III RWY 09L U/S, so use 27R. Great-circle distance to KJFK is 3,008 nm on a 288° initial bearing.

• Sample conversation for illustration only.

Connect once, then just ask - and get grounded answers from live aviation data.

A sample of the v3.1 endpoints exposed as callable tools - the model picks what it needs.

If it speaks the Model Context Protocol, it can connect to SkyLink.

Drop these into your client'smcpServersconfig and you're live.

One config block, every SkyLink endpoint as a tool - for Claude, Cursor, or any MCP client. Add your API key and start asking.

Access meteorological data for Portugal from the IPMA public API using natural language.

Provides accurate Islamic prayer times for locations throughout Malaysia using the waktusolat.app API.

A production-clean MCP server for the free Open-Meteo weather API (geocoding, forecast, air quality) with SRE-grade rate limiting, backoff, and structured logging.

Provides real-time weather alerts and detailed forecasts for US locations using the National Weather Service API.

Integrates the Korea Meteorological Administration's public weather API to provide climate data.

Fetches precipitation forecast data for a specific location using the Buienradar service.

GribStream MCP is a hosted Model Context Protocol server for weather forecast data. It helps AI agents discover GribStream datasets, resolve exact forecast variables and levels, validate request bodies, and build runnable GribStream Weather API requests for GFS, ECMWF IFS, NBM, HRRR, and other models.

62 real-time data tools for AI agents via MCP. Finance, crypto, FMCSA, sanctions, courts, weather, vehicles, cybersecurity. One bearer token, one bill. Free tier available.

The Meteomatics MCP server allows AI agents to securely access Meteomatics weather data tools.

Access global weather data and forecasts using the OpenMeteo API, including current conditions, historical data, and location search.