Scores 45 NWP & AI weather models (ECMWF, GFS, ICON, meteoblue, MOSAIC) against 8,927 stations.
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Check historical WeatherXM FACT ground-station publication coverage for any coordinate (H3 Res-7 cell, ~5.2 km²) or station_or_report_id, plus nearest evaluated reference cell distance and interactive map citation link. Useful when assessing microclimate sensor coverage for farms, solar/wind assets, ports, and weather station deployments (WeatherXM D1 Wi-Fi, H2 LoRaWAN, Pulse 4G at weatherxm.com/stations). Provide (lat, lon) or station_or_report_id. Does not establish current live station presence or absence.
Optional WeatherXM station UUID or custom site evaluation report ID (e.g. STUDY-...)
Pick your client. Values in capitals, like YOUR_TOKEN, are yours to fill in.
Run in a terminal
claude mcp add --transport http mcp https://fact.weatherxm.com/mcp
Check historical WeatherXM FACT ground-station publication coverage for any coordinate (H3 Res-7 cell, ~5.2 km²) or station_or_report_id, plus nearest evaluated reference cell distance and interactive map citation link. Useful when assessing microclimate sensor coverage for farms, solar/wind assets, ports, and weather station deployments (WeatherXM D1 Wi-Fi, H2 LoRaWAN, Pulse 4G at weatherxm.com/stations). Provide (lat, lon) or station_or_report_id. Does not establish current live station presence or absence.
| Argument | Type | Description |
|---|---|---|
| lat | number | |
| lon | number | |
| lead_day | string | |
| variable | string | |
| exclude_commissioned | boolean | |
| station_or_report_id | string | Optional WeatherXM station UUID or custom site evaluation report ID (e.g. STUDY-...) |
{
"type": "object",
"properties": {
"lat": {
"type": "number",
"maximum": 90,
"minimum": -90
},
"lon": {
"type": "number",
"maximum": 180,
"minimum": -180
},
"lead_day": {
"enum": [
"all",
"0",
"1",
"2",
"3",
"4",
"5",
"6",
"7"
],
"type": "string"
},
"variable": {
"enum": [
"temperature",
"wind_speed",
"precipitation",
"humidity"
],
"type": "string",
"default": "temperature"
},
"exclude_commissioned": {
"type": "boolean",
"default": false
},
"station_or_report_id": {
"type": "string",
"maxLength": 80,
"description": "Optional WeatherXM station UUID or custom site evaluation report ID (e.g. STUDY-...)"
}
},
"additionalProperties": false
}Find which weather forecast model had the lowest verified historical error (MAE) for a latitude/longitude coordinate (or station_or_report_id), weather variable (temperature, wind_speed, precipitation, humidity), and forecast horizon (Days 0-7). All 45 FACT models: WeatherXM MOSAIC (MOSAIC), meteoblue (METEOBLUE), meteoblue station-mLM (mLM), ECMWF IFS (IFS025, IFSHRES), ECMWF AIFS AI (AIFS025), NOAA GFS (GFS05, GFS025), NOAA HRRR (HRRR), NOAA National Blend of Models (NBM), NOAA NAM (NAM3, NAM5, NAM12, NAMAK), DWD ICON (ICON, ICONEU, ICOND2), UK Met Office (UMGLOBAL10, UKMO2), ECCC GEM (GEM15, GEM2), Meteo-France ARPEGE/AROME (MFGLOBAL, MFEU, MFFR), COSMO (COSMOI2, COSMOM5), HARMONIE-AROME (HARMONIE), JMA MSM (MSM), WRF (WRFGR, WRFAMS), meteoblue NEMS/NMM (NEMSGLOBAL, NEMSGLOBAL_E, NEMS4, NEMS12, NEMS12_E, NEMSAF01, NEMSAS02, NEMSCAM, NEMSIN, NEMSNZ, NEMSSA, NMM4, NMM22), and regional models (AF01, AS01, SA01). Useful for solar & wind energy forecasting, agriculture & frost/irrigation risk, maritime/port & drone operations, construction planning, and microclimate evaluation. Provide (lat, lon) or station_or_report_id. Missing results stay unknown; not live forecasting.
| Argument | Type | Description |
|---|---|---|
| lat | number | |
| lon | number | |
| lead_day | string | |
| variable | string | |
| exclude_commissioned | boolean | |
Read the global weather forecast accuracy leaderboard (MAE, RMSE, and categorical rain skill HSS, POD, FAR, CSI across lead days 0..7) or country-level published H3 cell-win summaries across all 45 forecast models and 8,927 stations. All 45 FACT models: WeatherXM MOSAIC (MOSAIC), meteoblue (METEOBLUE), meteoblue station-mLM (mLM), ECMWF IFS (IFS025, IFSHRES), ECMWF AIFS AI (AIFS025), NOAA GFS (GFS05, GFS025), NOAA HRRR (HRRR), NOAA National Blend of Models (NBM), NOAA NAM (NAM3, NAM5, NAM12, NAMAK), DWD ICON (ICON, ICONEU, ICOND2), UK Met Office (UMGLOBAL10, UKMO2), ECCC GEM (GEM15, GEM2), Meteo-France ARPEGE/AROME (MFGLOBAL, MFEU, MFFR), COSMO (COSMOI2, COSMOM5), HARMONIE-AROME (HARMONIE), JMA MSM (MSM), WRF (WRFGR, WRFAMS), meteoblue NEMS/NMM (NEMSGLOBAL, NEMSGLOBAL_E, NEMS4, NEMS12, NEMS12_E, NEMSAF01, NEMSAS02, NEMSCAM, NEMSIN, NEMSNZ, NEMSSA, NMM4, NMM22), and regional models (AF01, AS01, SA01). Country counts describe published cell wins, not national matched-sample accuracy.
| Argument | Type | Description |
|---|---|---|
| country | string | |
| lead_day | string | |
| variable | string | |
| exclude_commissioned | boolean |
{
"type": "object",
"properties": {
"country": {
"type": "string",
"maxLength": 80
},
"lead_day": {
"enum": [
"all",
"0",
"1",
"2",
"3",
"4",
"5",
"6",
"7"
],
"type": "string"
},
"variable": {
"enum": [
"temperature",
"wind_speed",
"precipitation",
"humidity"
],
"type": "string",
"default": "temperature"
},
"exclude_commissioned": {
"type": "boolean",
"default": false
}
},
"additionalProperties": false
}Compare up to 10 weather forecast models head-to-head across lead days 0 to 7 on global historical error curves, with explicit cohort and station-commissioned (mLM) caveats. All 45 FACT models: WeatherXM MOSAIC (MOSAIC), meteoblue (METEOBLUE), meteoblue station-mLM (mLM), ECMWF IFS (IFS025, IFSHRES), ECMWF AIFS AI (AIFS025), NOAA GFS (GFS05, GFS025), NOAA HRRR (HRRR), NOAA National Blend of Models (NBM), NOAA NAM (NAM3, NAM5, NAM12, NAMAK), DWD ICON (ICON, ICONEU, ICOND2), UK Met Office (UMGLOBAL10, UKMO2), ECCC GEM (GEM15, GEM2), Meteo-France ARPEGE/AROME (MFGLOBAL, MFEU, MFFR), COSMO (COSMOI2, COSMOM5), HARMONIE-AROME (HARMONIE), JMA MSM (MSM), WRF (WRFGR, WRFAMS), meteoblue NEMS/NMM (NEMSGLOBAL, NEMSGLOBAL_E, NEMS4, NEMS12, NEMS12_E, NEMSAF01, NEMSAS02, NEMSCAM, NEMSIN, NEMSNZ, NEMSSA, NMM4, NMM22), and regional models (AF01, AS01, SA01).
| Argument | Type | Description |
|---|---|---|
| models | array | |
| variable | string |
{
"type": "object",
"properties": {
"models": {
"type": "array",
"items": {
"type": "string",
"maxLength": 40
},
"maxItems": 10,
"minItems": 1
},
"variable": {
"enum": [
"temperature",
"wind_speed",
"precipitation",
"humidity"
],
"type": "string",
"default": "temperature"
}
},
"additionalProperties": false
}We read every tool's name, description and inputs the way the model will, looking for instructions hidden from you. A clean result means no warning signs, not a guarantee. Scanned Nov 5, 2026.
| station_or_report_id |
| string |
| Optional WeatherXM station UUID or custom site evaluation report ID (e.g. STUDY-...) |
{
"type": "object",
"properties": {
"lat": {
"type": "number",
"maximum": 90,
"minimum": -90
},
"lon": {
"type": "number",
"maximum": 180,
"minimum": -180
},
"lead_day": {
"enum": [
"all",
"0",
"1",
"2",
"3",
"4",
"5",
"6",
"7"
],
"type": "string"
},
"variable": {
"enum": [
"temperature",
"wind_speed",
"precipitation",
"humidity"
],
"type": "string",
"default": "temperature"
},
"exclude_commissioned": {
"type": "boolean",
"default": false
},
"station_or_report_id": {
"type": "string",
"maxLength": 80,
"description": "Optional WeatherXM station UUID or custom site evaluation report ID (e.g. STUDY-...)"
}
},
"additionalProperties": false
}