mcp-meteoblue
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| METEOBLUE_API_KEY | Yes | Your meteoblue API key |
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 |
|---|---|
| search_locationsB | Resolve a city, place, postal code, IATA code, or ICAO code to coordinates and elevation using the meteoblue Location Search API. |
| get_forecastA | Get meteoblue forecast JSON by place name or coordinates. Place names are resolved through the Location Search API. Only packages documented for the Free Weather API are accepted. |
| get_forecast_imageA | Generate a meteoblue forecast meteogram by place name or coordinates. Returns the PNG directly. Image access depends on the API key's meteoblue entitlement. |
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 3 tools
Each tool has a clearly distinct purpose: location resolution, raw forecast data, and forecast image generation. The two forecast tools are differentiated by output format (JSON vs PNG), so there is no practical ambiguity.
All tool names follow a consistent verb_noun pattern: search_locations, get_forecast, get_forecast_image. The naming clearly communicates both the action and the target.
Three tools is well-scoped for a small weather API server: one for geocoding, one for data, one for imagery. Each tool serves a distinct step in the core location-to-forecast workflow.
The surface covers the essential meteorology workflow: resolve a location, retrieve forecast data, and generate a forecast image. A minor gap is the lack of separate current-conditions or historical-weather tools, but forecasts likely include current data and the core purpose is well covered.