Weather MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_current_weatherC | Récupère la météo actuelle pour une ville (Sydney par défaut) |
| get_weather_forecastC | Récupère les prévisions météo sur 7 jours (Sydney par défaut) |
| get_weather_by_coordinatesC | Récupère la météo selon les coordonnées géographiques |
| search_citiesC | Recherche des villes par nom pour obtenir leurs coordonnées |
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 4 tools
Each tool has a clearly distinct purpose: get_current_weather for current conditions by city, get_weather_by_coordinates for current conditions by coordinates, get_weather_forecast for multi-day forecasts, and search_cities for city lookup. There is no overlap or ambiguity between these functions.
All tool names follow a consistent verb_noun pattern using snake_case: get_current_weather, get_weather_by_coordinates, get_weather_forecast, and search_cities. The naming is predictable and readable throughout.
With 4 tools, this is well-scoped for a weather server. Each tool serves a distinct and necessary function (current weather by location, current weather by coordinates, forecasts, and city search), making the count appropriate without being too sparse or bloated.
The tool set covers core weather operations well: retrieving current weather (by city and coordinates), forecasts, and city search for location resolution. A minor gap is the lack of historical weather data or more granular forecast options, but agents can work effectively with the provided tools for most use cases.