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_alertsA | Get weather alerts for a US state. |
| get_forecastB | Get weather forecast for a location. |
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 2 tools
The two tools have clearly distinct purposes: get_alerts retrieves alerts for US states, while get_forecast provides forecasts for geographic coordinates. There is no overlap in functionality or ambiguity about which tool to use for each task.
Both tools follow a consistent verb_noun naming pattern (get_alerts, get_forecast) with identical verb usage and snake_case formatting. The naming is perfectly predictable and uniform across the tool set.
With only two tools, this server feels under-scoped for a weather domain. While alerts and forecasts are core functions, there are obvious gaps like current conditions, historical data, or radar imagery that would make the tool set more complete and useful.
The tool set is severely incomplete for a weather server. It lacks basic operations like getting current weather conditions, historical data, or radar information. The two tools provided create dead ends for common agent workflows that require more comprehensive weather data.