Open-Meteo MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPEN_METEO_API_URL | No | Base URL for Open-Meteo forecast API | https://api.open-meteo.com |
| OPEN_METEO_MARINE_API_URL | No | Marine weather API URL | https://marine-api.open-meteo.com |
| OPEN_METEO_ARCHIVE_API_URL | No | Historical data API URL | https://archive-api.open-meteo.com |
| OPEN_METEO_ENSEMBLE_API_URL | No | Ensemble forecast API URL | https://ensemble-api.open-meteo.com |
| OPEN_METEO_SEASONAL_API_URL | No | Seasonal forecast API URL | https://seasonal-api.open-meteo.com |
| OPEN_METEO_GEOCODING_API_URL | No | Geocoding API URL | https://geocoding-api.open-meteo.com |
| OPEN_METEO_AIR_QUALITY_API_URL | No | Air quality API URL | https://air-quality-api.open-meteo.com |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| weather_forecastA | Get weather forecast data for coordinates using Open-Meteo API. Supports hourly and daily data with various weather variables. When no |
| weather_archiveB | Get historical weather data from ERA5 reanalysis (1940-present) for specific coordinates and date range. |
| air_qualityB | Get air quality forecast data including PM2.5, PM10, ozone, nitrogen dioxide, pollen, European/US AQI indices, UV index and other pollutants. |
| marine_weatherC | Get marine weather forecast including wave height, wave period, wave direction and sea surface temperature. |
| elevationA | Get elevation data for given coordinates using digital elevation models. Supports batch lookups: pass arrays of the same length for latitude and longitude to query multiple points in one call. |
| flood_forecastC | Get river discharge and flood forecasts from GloFAS (Global Flood Awareness System). |
| geocodingA | Search for locations worldwide by place name or postal code. Returns geographic coordinates (latitude and longitude) and detailed location information. Use this tool when you need to convert a location name (e.g., "Paris", "New York") into precise coordinates (latitude/longitude) that are required by other tools. This is essential when you have a location name but need coordinates for data fetching tools. |
| dwd_icon_forecastA | Get weather forecast from German DWD ICON model. IMPORTANT: Specify exactly one DWD model in the |
| gfs_forecastA | Get weather forecast from US NOAA GFS model. IMPORTANT: Specify exactly one GFS model in the |
| meteofrance_forecastA | Get weather forecast from French Météo-France models. IMPORTANT: Specify exactly one Météo-France model in the |
| ecmwf_forecastA | Get weather forecast from ECMWF models via the dedicated /v1/ecmwf endpoint. IMPORTANT: Specify exactly one model in the |
| jma_forecastA | Get weather forecast from Japan Meteorological Agency (JMA) models. IMPORTANT: Specify exactly one JMA model in the |
| metno_forecastA | Get weather forecast from Norwegian Meteorological Institute models. The |
| gem_forecastA | Get weather forecast from Canadian Meteorological Centre (GEM) models. IMPORTANT: Specify exactly one GEM model in the |
| seasonal_forecastB | Get long-range seasonal forecasts for temperature and precipitation up to ~7 months ahead. |
| climate_projectionC | Get climate change projections from CMIP6 models for different warming scenarios. |
| ensemble_forecastB | Get ensemble forecasts showing forecast uncertainty with multiple model runs. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 17 tools
The provider-specific forecast tools (gfs_forecast, ecmwf_forecast, jma_forecast, dwd_icon_forecast, gem_forecast, metno_forecast, meteofrance_forecast) overlap heavily with the generic weather_forecast, which also returns model data. Descriptions clarify that provider tools are for multi-model comparison, but the boundary between picking weather_forecast and a specific provider tool is not always obvious. Other tools (air_quality, marine_weather, elevation, flood_forecast, geocoding) are clearly distinct.
Names are consistently lowercase snake_case, which is good, but the pattern is mixed: some use {provider}_forecast (gfs_forecast), others use bare domain nouns (air_quality, elevation, geocoding), and weather_forecast/weather_archive use a weather_ prefix. Still readable and mostly predictable.
17 tools is on the heavy side, and seven of them are near-duplicate provider-specific forecast endpoints that largely could have been a single parameterized forecast tool. The remaining domain tools (air quality, marine, flood, elevation, geocoding, archive, seasonal, climate) each earn their place.
Coverage is broad and complete for a weather API: current/forecast, ensemble, seasonal, climate projections, historical archive, air quality, marine, flood, and elevation. Minor gaps like no explicit 'current conditions' or station/observation tool, but core lifecycle is well covered.