mcp-weather-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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_currentA | Current conditions for a city: temperature, feels-like, humidity, wind, precipitation. |
| get_forecastA | Daily forecast for a city: min/max temperature, rain chance and amount, max wind. |
| compare_citiesA | Current weather side by side for 2-5 cities, with the warmest and coldest named. |
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 targets a distinct temporal or comparative view (current, forecast, multi-city comparison), and descriptions make the boundaries explicit. compare_cities partially overlaps with get_current applied to several cities, but the added ranking output justifies its separate existence.
All three tools follow the same snake_case verb_noun pattern (get_current, get_forecast, compare_cities). The verbs are accurate and predictable, so an agent can guess a tool's intent from its name.
Three tools is on the lean side, but each covers a genuinely distinct weather-query pattern and nothing feels redundant. It sits at the low edge of a well-scoped surface rather than being thin to the point of uselessness.
The core weather workflows (current conditions, daily outlook, multi-city comparison) are covered with no dead ends. Gaps exist around hourly breakdowns, historical data, alerts, and city/geocoding lookup, but agents can work around these for typical queries.