Aviation MCP bietet eine Reihe von Model Context Protocol (MCP)-Servern, die auf FAA- und andere Luftfahrt-APIs abgebildet werden. Dadurch können Echtzeit-Luftfahrtdaten problemlos in Ihre LLM-basierten Workflows integriert werden. Dieses Projekt richtet sich an Entwickler, die ihre LLM-Clients (wie Cursor, Claude oder andere) mit maßgeblichen Luftfahrtdatenquellen für Wetter, NOTAMs, Karten, Flugzeuginformationen und mehr verbinden möchten.
⚠️ Haftungsausschluss ⚠️
Der Entwickler dieses Codes übernimmt keine Verantwortung für die Richtigkeit oder Sicherheit der datenliefernden APIs oder Ihrer Flugplanung. Dies gilt sowohl für die Software als auch für die Anweisungen in FlightPlanning.md . Diese ersetzen NICHT die Expertise eines entsprechend lizenzierten Piloten . Der verantwortliche Pilot trägt die alleinige Verantwortung für die Flugsicherheit und die Einhaltung aller relevanten Vorschriften.
Modulare MCP-Server für Luftfahrtdaten
Integriert mit FAA, Aviation Weather und anderen APIs
Einfache Konfiguration zur Verwendung mit jedem MCP-kompatiblen LLM-Client
Veröffentlicht als npm-Paket: aviation-mcp
Related MCP server: Aviation MCP Server
Fügen Sie den Aviation-MCP-Server wie folgt zu Ihrer mcp.json hinzu. Aktualisieren Sie die Schlüssel, sodass sie gültige Werte enthalten (besuchen Sie https://api.faa.gov/s/ für FAA-API-Client-Anmeldeinformationen, https://api-ninjas.com/ für deren API-Schlüssel) oder entfernen Sie sie (die entsprechenden APIs werden dann ausgeblendet).
Flugwetterdaten (einschließlich vieler georeferenzierter Daten) und Karten benötigen keine API-Schlüssel. NOTAMs erfordern eine FAA-Client-ID/ein FAA-Client-Geheimnis.
{
"mcpServers": {
"aviation": {
"command": "npx",
"args": [
"-y",
"aviation-mcp"
],
"env": {
"API_NINJA_KEY": "<your-key>",
"FAA_CLIENT_ID": "<your-id>",
"FAA_CLIENT_SECRET": "<your-secret>"
}
}
}
}Wetter : Flugwetterdaten (METAR, TAF, PIREP, SIGMET, G-AIRMET usw.)
Karten : Sectional-, TAC-, IFR-Enroute- und TPP-Karten
Notam : FAA NOTAM API
Diese Quellen wären hilfreich, aber die Integration bzw. der API-Zugriff funktioniert noch nicht:
Niederschlag : FAA EIM Weather Proximity API (Niederschlagsdaten)
Flughäfen : Informationen zu Flughäfen und Start- und Landebahnen der FAA
Verspätungen : Die ASWS FAA API bietet Informationen zu Flughafenverspätungen.
Flugzeuge : Flugzeugdaten
Prozedurrouten in einem maschinenlesbaren Format. TODO: Laden Sie CIFP-Daten herunter und verwenden Sie etwas wie arinc424 , um sie in ein verwendbares Format zu konvertieren.
Luftraumdaten in einem maschinenlesbaren Format. TODO: Laden Sie NASR-Daten herunter und verwenden Sie eine Bibliothek zum Lesen von Shapefiles und/oder AIXM-Daten.
Nach der Konfiguration kann Ihr LLM-Client eine Verbindung zu den MCP-Servern herstellen und bei Bedarf Luftfahrtdaten abfragen. Weitere Informationen zur Bereitstellung der mcp.json Konfiguration finden Sie in der Dokumentation Ihres Clients.
Unter FlightPlanning.md finden Sie ein Beispiel für eine Systemaufforderung zur Flugplanung.
Für ein zeitliches Bewusstsein empfehle ich die Kombination mit Zeit .
Erwägen Sie für die EFB-Verwaltung eine Kombination mit filesystem oder gdrive .
Eine detaillierte Liste der unterstützten APIs, Endpunkte und Integrationsstatus finden Sie unter Sources.md .
MIT
Retrieves NOTAMs based on specified filters
| Name | Required | Description | Default |
|---|---|---|---|
| classification | No | The NOTAM classification | |
| domesticLocation | No | The domestic location criteria (e.g., 'IAD' for Dulles International Airport) | |
| effectiveEndDate | No | The effective end date | |
| effectiveStartDate | No | The effective start date | |
| featureType | No | The feature type filter | |
| icaoLocation | No | The ICAO location criteria (e.g., 'KIAD' for Dulles International Airport) | |
| lastUpdatedDate | No | The last update date | |
| locationLatitude | No | The location latitude (e.g., 60.57) | |
| locationLongitude | No | The location longitude (e.g., -151.24) | |
| locationRadius | No | The location radius in nautical miles (max: 100) | |
| notamNumber | No | The NOTAM number (e.g., 'CK0000/01') | |
| notamType | No | The NOTAM type: 'N' for New, 'R' for Replaced, 'C' for Canceled | |
| pageNum | No | The page number | |
| pageSize | No | The page size (max: 1000) | |
| responseFormat | No | Response format for NOTAM data | geoJson |
| sortBy | No | The field to sort results by | |
| sortOrder | No | The sort order |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states retrieval with filters. It lacks behavioral details like pagination handling (implied by pageNum/pageSize but not explained), rate limits, authentication needs, or response format implications (e.g., geoJson output). This leaves significant gaps in understanding tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and scope without unnecessary words. It's appropriately sized for its purpose, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 17 parameters, no annotations, and no output schema, the description is inadequate. It doesn't address behavioral aspects like pagination, response formats, or error handling, leaving the agent with insufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds no extra meaning beyond implying filters exist, which the schema already details. Baseline 3 is appropriate as the schema handles parameter semantics effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('NOTAMs'), with scope ('based on specified filters'). It's specific about the action and subject matter, though without sibling tools to differentiate from, it can't achieve the highest score for sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool, such as scenarios or prerequisites. The description mentions filters but doesn't explain their application or alternatives, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0get_notamsScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'get_notams' has a clear, distinct purpose focused on retrieving NOTAMs.
The tool name 'get_notams' follows a clear verb_noun pattern (get + notams). Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions.
The server has only one tool, which feels thin for a domain like aviation that typically involves multiple operations such as querying weather, flight plans, or airspace data. This minimal toolset limits functionality and suggests an incomplete surface.
The toolset is severely incomplete for an aviation context. It only provides NOTAM retrieval, with no coverage for other essential aviation data like METARs, TAFs, flight tracking, or airspace information, leading to significant gaps in agent workflows.
Aircraft intelligence for AI agents: valuations with uncertainty bands, FAA registry lookups, cost of ownership, comparable aircraft, fleet search, airworthiness directives and STCs, market metrics and forecasts, verified value reports, pre-buy diligence checklists, logbook search and a watchlist. 38 tools; free tier with OAuth or a Windsock API key.
Aviationstack MCP — global flight + airport + airline data
Aviation identity resolution and an AI use-case atlas, with provenance and temporal validity
350+ production-ready APIs through one MCP server — weather, geocoding, validation, financial data.
