{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_ahmed2real-thinkzone","slug":"ahmed2real-thinkzone","name":"NWS Weather & Aviation","type":"mcp","url":"https://smithery.ai/servers/ahmed2real/thinkzone","page_url":"https://unfragile.ai/ahmed2real-thinkzone","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","weather","smithery:ahmed2real/thinkzone"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_ahmed2real-thinkzone__cap_0","uri":"capability://data.processing.analysis.real.time.nws.grid.point.forecast.retrieval.with.location.aware.metadata","name":"real-time nws grid point forecast retrieval with location-aware metadata","description":"Fetches gridded weather forecasts from the National Weather Service API by converting geographic coordinates (latitude/longitude) into NWS grid points, then retrieving hourly or 12-hourly forecast periods with temperature, precipitation, wind, and hazard data. Uses NWS's native grid system rather than polling multiple weather stations, enabling precise forecasts for any US location with associated metadata (forecast office, grid coordinates, elevation).","intents":["Get detailed hourly weather forecasts for a specific latitude/longitude without managing multiple data sources","Build location-aware weather features that automatically resolve to the correct NWS forecast grid","Retrieve forecast metadata including responsible forecast office and grid cell information for audit/transparency"],"best_for":["Developers building location-based weather applications or LLM agents","Teams integrating NWS data into existing geospatial systems","Non-technical builders prototyping weather-aware features via MCP clients"],"limitations":["Limited to continental US, Alaska, Hawaii, and US territories — international locations return errors","Forecast resolution is NWS grid cell (~2.5km), not arbitrary point precision","Forecast periods are fixed by NWS (typically 12-hourly for extended forecasts, hourly for short-term) — custom time intervals require client-side interpolation"],"requires":["MCP client compatible with Model Context Protocol (Claude, custom agents, etc.)","Valid US latitude/longitude coordinates","Network access to api.weather.gov (NWS public API, no authentication required)"],"input_types":["latitude (float, -90 to 90)","longitude (float, -180 to 180)"],"output_types":["structured JSON with forecast periods, temperature, precipitation probability, wind speed/direction, hazards"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_1","uri":"capability://data.processing.analysis.active.weather.alerts.and.hazard.retrieval.by.geographic.zone","name":"active weather alerts and hazard retrieval by geographic zone","description":"Queries the NWS alerts API to retrieve active weather warnings, watches, and advisories for specified geographic areas (counties, marine zones, fire weather zones, or bounding boxes). Returns structured alert data including event type, severity, effective/expiration times, headline, and detailed description. Supports filtering by zone type and geographic extent without requiring manual zone code lookup.","intents":["Display active weather alerts for a user's location or region in a weather-aware application","Build alert-triggered automation (e.g., notify users when severe thunderstorm warning is issued for their area)","Retrieve detailed hazard descriptions and recommended actions from official NWS alerts"],"best_for":["Developers building consumer weather apps or emergency notification systems","Teams integrating NWS alerts into IoT/smart home systems","Builders creating location-aware safety features for outdoor activities"],"limitations":["Alert data is updated by NWS on their schedule (typically 5-10 minute latency from issuance)","Geographic filtering is limited to predefined NWS zone types (counties, marine zones, etc.) — arbitrary polygon queries not supported","Alert descriptions are plain text from NWS; no structured hazard severity scoring or custom risk assessment"],"requires":["MCP client with Model Context Protocol support","Valid NWS zone identifier (county FIPS code, marine zone code, etc.) OR latitude/longitude for automatic zone resolution","Network access to api.weather.gov/alerts"],"input_types":["zone identifier (string, e.g., 'UScz001' for Cochise County, AZ)","latitude/longitude (float pair for automatic zone lookup)"],"output_types":["JSON array of alert objects with event type, severity, effective/expiration times, headline, description"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_2","uri":"capability://data.processing.analysis.aviation.taf.and.sigmet.retrieval.for.flight.planning","name":"aviation taf and sigmet retrieval for flight planning","description":"Fetches Terminal Aerodrome Forecasts (TAFs) and Significant Meteorological Information (SIGMETs) from NWS aviation products, providing structured wind, visibility, weather, and hazard data for specific airports or regions. TAFs are decoded from raw ICAO format into structured fields (wind direction/speed, visibility, weather phenomena, validity periods). SIGMETs include convective, non-convective, and urgent weather information for flight planning.","intents":["Retrieve TAF data for a specific airport to inform flight planning decisions","Get active SIGMETs for a region to identify en-route hazards (turbulence, icing, convection)","Build aviation-specific weather features that decode raw TAF/SIGMET text into structured, queryable data"],"best_for":["Developers building flight planning tools or aviation weather apps","Teams integrating NWS aviation products into EFB (Electronic Flight Bag) systems","Builders creating pilot briefing or pre-flight decision support tools"],"limitations":["TAF data is issued on a fixed schedule (typically every 6 hours) — real-time updates not available between issuances","SIGMET coverage is limited to continental US and some offshore areas — international airspace not covered","Raw TAF/SIGMET text requires decoding; this MCP may provide raw ICAO format requiring client-side parsing for full detail extraction"],"requires":["MCP client compatible with Model Context Protocol","Valid ICAO airport identifier (4-letter code, e.g., 'KJFK' for New York JFK)","Network access to NWS aviation product endpoints (api.weather.gov or aviation.weather.gov)"],"input_types":["ICAO airport code (string, 4 characters)","geographic region identifier for SIGMET queries"],"output_types":["Structured JSON with TAF periods (wind, visibility, weather, validity times) and SIGMET data (phenomenon type, area, validity)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_3","uri":"capability://image.visual.radar.and.satellite.imagery.retrieval.by.location","name":"radar and satellite imagery retrieval by location","description":"Retrieves links to NWS radar and satellite imagery products (reflectivity, velocity, satellite IR/visible) for specified locations or regions. Returns URLs to current and recent radar/satellite images, enabling integration of visual weather data into applications. May include metadata on image validity times and product types (base reflectivity, velocity, satellite IR, etc.).","intents":["Display current radar or satellite imagery for a location in a weather app or dashboard","Retrieve recent radar loops to show storm movement and intensity trends","Integrate NWS visual weather products into LLM agents for weather analysis and description"],"best_for":["Developers building consumer weather apps with visual components","Teams creating weather dashboards or monitoring systems","Builders integrating visual weather context into AI agents for weather analysis"],"limitations":["Imagery is provided as URLs to external NWS servers; client must handle image fetching and caching","Image update frequency depends on NWS radar/satellite schedule (typically 5-10 minute intervals for radar)","No direct image processing or analysis provided — client must implement custom image parsing or use external vision models"],"requires":["MCP client with Model Context Protocol support","Valid location identifier (latitude/longitude or NWS radar site code)","Network access to NWS imagery servers (radar.weather.gov or similar)"],"input_types":["latitude/longitude (float pair)","NWS radar site identifier (string, e.g., 'KJFK' for nearest radar)"],"output_types":["JSON with imagery URLs, product types, validity times, and metadata"],"categories":["image-visual","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_4","uri":"capability://data.processing.analysis.station.observation.data.retrieval.for.current.conditions","name":"station observation data retrieval for current conditions","description":"Fetches current and recent observations from NWS weather stations (METAR-equivalent data) for specified locations, including temperature, dew point, wind, visibility, pressure, and weather phenomena. Automatically resolves location coordinates to the nearest reporting station and returns structured observation data with timestamp and station metadata.","intents":["Get current weather conditions (temperature, wind, visibility) for a location without parsing raw METAR","Retrieve station metadata (elevation, location name) for context in weather applications","Build real-time weather displays that update with latest station observations"],"best_for":["Developers building weather apps requiring current conditions display","Teams integrating real-time weather data into IoT or smart home systems","Builders creating weather-aware features that need precise, station-based observations"],"limitations":["Station observations are updated on a schedule (typically hourly for most stations, more frequent for major airports) — not true real-time","Coverage is limited to US and territories; international stations not available","Nearest station may be 10-50+ km away depending on location; no interpolation between stations"],"requires":["MCP client compatible with Model Context Protocol","Valid US latitude/longitude or station identifier (ICAO code)","Network access to api.weather.gov/stations"],"input_types":["latitude/longitude (float pair)","station identifier (ICAO code, e.g., 'KJFK')"],"output_types":["JSON with temperature, dew point, wind speed/direction, visibility, pressure, weather phenomena, timestamp, station metadata"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_5","uri":"capability://data.processing.analysis.zone.based.product.retrieval.fire.weather.marine.etc","name":"zone-based product retrieval (fire weather, marine, etc.)","description":"Retrieves NWS zone-specific products including fire weather outlooks, marine forecasts, and zone-based hazard information for predefined geographic zones (fire weather zones, marine zones, county zones). Automatically resolves location coordinates to applicable zones and returns structured product data with validity periods and hazard details.","intents":["Get fire weather outlook or marine forecast for a specific zone without manual zone code lookup","Retrieve zone-specific hazard information (e.g., high wind watches for a marine zone)","Build location-aware features that automatically identify and retrieve relevant zone products"],"best_for":["Developers building specialized weather apps (marine, fire weather, outdoor recreation)","Teams integrating NWS zone products into domain-specific systems (wildfire management, marine operations)","Builders creating location-aware hazard or safety features"],"limitations":["Zone products are issued on NWS schedules (fire weather outlooks typically issued once daily, marine forecasts multiple times daily) — not real-time","Zone definitions are fixed by NWS; custom geographic boundaries not supported","Product availability varies by zone type and region; not all zones have all product types"],"requires":["MCP client with Model Context Protocol support","Valid location identifier (latitude/longitude or zone code)","Network access to NWS zone product endpoints"],"input_types":["latitude/longitude (float pair)","zone identifier (string, e.g., fire weather zone code)"],"output_types":["JSON with zone product data, validity periods, hazard information, and zone metadata"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_6","uri":"capability://tool.use.integration.mcp.based.tool.integration.for.llm.agents.and.ai.systems","name":"mcp-based tool integration for llm agents and ai systems","description":"Exposes all NWS weather capabilities through the Model Context Protocol (MCP), enabling Claude, custom LLM agents, and other AI systems to directly query weather data, alerts, and forecasts as part of their reasoning and response generation. MCP integration provides structured tool definitions, automatic parameter validation, and seamless context passing between the LLM and NWS APIs.","intents":["Enable Claude or custom LLM agents to answer weather questions by directly querying NWS data","Build AI-powered weather assistants that retrieve current conditions, forecasts, and alerts in response to natural language queries","Integrate weather context into LLM agents for decision-making (e.g., flight planning, outdoor activity recommendations)"],"best_for":["Developers building LLM agents and AI assistants that need weather context","Teams integrating weather intelligence into Claude-based applications","Builders creating conversational weather interfaces or AI-powered decision support systems"],"limitations":["MCP integration adds ~100-200ms latency per tool call due to protocol overhead and NWS API response times","LLM agents may misinterpret weather data or make incorrect decisions based on incomplete context; requires careful prompt engineering","Tool definitions are fixed by the MCP server; custom tool parameters or filtering not supported without modifying the server"],"requires":["MCP-compatible LLM client (Claude via Claude Desktop, custom agents with MCP support)","MCP server running (this artifact, ahmed2real/thinkzone)","Network access from MCP client to MCP server and from server to api.weather.gov"],"input_types":["Natural language queries from LLM (translated to structured tool calls by MCP)","Structured tool parameters (latitude, longitude, zone codes, etc.)"],"output_types":["Structured JSON responses from NWS APIs, formatted as MCP tool results for LLM consumption"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahmed2real-thinkzone__cap_7","uri":"capability://data.processing.analysis.automatic.location.to.grid.point.resolution.with.metadata.enrichment","name":"automatic location-to-grid-point resolution with metadata enrichment","description":"Automatically converts arbitrary latitude/longitude coordinates into NWS grid points and retrieves associated metadata (forecast office, grid cell coordinates, elevation, timezone, county/zone information). This resolution happens transparently when querying forecasts or products, eliminating the need for clients to manually perform grid lookups or maintain coordinate-to-zone mappings.","intents":["Query weather forecasts for any US coordinate without manually looking up the NWS grid point","Retrieve forecast office and zone information for a location to understand which NWS office is responsible","Build location-aware features that automatically resolve geographic coordinates to NWS administrative boundaries"],"best_for":["Developers building location-based weather features who want to avoid manual grid lookups","Teams integrating NWS data into geospatial systems that work with arbitrary coordinates","Builders creating multi-location weather dashboards or regional monitoring systems"],"limitations":["Resolution is limited to US and territories; international coordinates return errors","Grid point resolution adds ~50-100ms latency per query (requires additional API call to NWS points endpoint)","Metadata is limited to what NWS provides (forecast office, grid coordinates, elevation); no custom enrichment or third-party data fusion"],"requires":["MCP client with Model Context Protocol support","Valid US latitude/longitude coordinates","Network access to api.weather.gov/points endpoint"],"input_types":["latitude (float, -90 to 90)","longitude (float, -180 to 180)"],"output_types":["JSON with grid point coordinates, forecast office, elevation, timezone, county/zone codes, and other NWS metadata"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"moderate","permissions":["MCP client compatible with Model Context Protocol (Claude, custom agents, etc.)","Valid US latitude/longitude coordinates","Network access to api.weather.gov (NWS public API, no authentication required)","MCP client with Model Context Protocol support","Valid NWS zone identifier (county FIPS code, marine zone code, etc.) OR latitude/longitude for automatic zone resolution","Network access to api.weather.gov/alerts","MCP client compatible with Model Context Protocol","Valid ICAO airport identifier (4-letter code, e.g., 'KJFK' for New York JFK)","Network access to NWS aviation product endpoints (api.weather.gov or aviation.weather.gov)","Valid location identifier (latitude/longitude or NWS radar site code)"],"failure_modes":["Limited to continental US, Alaska, Hawaii, and US territories — international locations return errors","Forecast resolution is NWS grid cell (~2.5km), not arbitrary point precision","Forecast periods are fixed by NWS (typically 12-hourly for extended forecasts, hourly for short-term) — custom time intervals require client-side interpolation","Alert data is updated by NWS on their schedule (typically 5-10 minute latency from issuance)","Geographic filtering is limited to predefined NWS zone types (counties, marine zones, etc.) — arbitrary polygon queries not supported","Alert descriptions are plain text from NWS; no structured hazard severity scoring or custom risk assessment","TAF data is issued on a fixed schedule (typically every 6 hours) — real-time updates not available between issuances","SIGMET coverage is limited to continental US and some offshore areas — international airspace not covered","Raw TAF/SIGMET text requires decoding; this MCP may provide raw ICAO format requiring client-side parsing for full detail extraction","Imagery is provided as URLs to external NWS servers; client must handle image fetching and caching","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.56507748644873,"quality":0.41,"ecosystem":0.42,"match_graph":0.25,"freshness":0.5,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:25.635Z","last_scraped_at":"2026-05-03T15:18:28.633Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=ahmed2real-thinkzone","compare_url":"https://unfragile.ai/compare?artifact=ahmed2real-thinkzone"}},"signature":"juIA8CyMLvpANRiSw0Ahth8ePacPhyX70deodCExP4MCioHmJ9JS0csEcYfEf52Tt3zP/z+523IkEPnx27S0BQ==","signedAt":"2026-06-22T01:49:08.363Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ahmed2real-thinkzone","artifact":"https://unfragile.ai/ahmed2real-thinkzone","verify":"https://unfragile.ai/api/v1/verify?slug=ahmed2real-thinkzone","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}