com.weatherxm.fact/mcp · v2.1.0 · location-and-travel
WeatherXM FACT — Forecast Accuracy & Ground-Truth Verification is healthy: it completed an MCP handshake in 803 ms and exposes 4 tools.
Scores 45 NWP & AI weather models (ECMWF, GFS, ICON, meteoblue, MOSAIC) against 8,927 stations.
Endpoint: https://fact.weatherxm.com/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 4 |
| Latency | 803 ms |
| Last checked (UTC) | 2026-11-05T08:55:45.641Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-11-05T08:55:45.641Z | Healthy | 803 |
get_best_forecast_model | 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), meteobl |
check_ground_truth_coverage | 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, |
get_fact_leaderboard | 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 (METEOBLU |
get_model_head_to_head | 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) |