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_alertsB | Get weather alerts for a US state. |
| get_forecastC | 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 between them.
Both tools follow a consistent verb_noun pattern (get_alerts, get_forecast) with identical verb usage and snake_case formatting. The naming is perfectly predictable across the tool set.
With only 2 tools, the server feels thin for a weather domain. While alerts and forecasts are core features, obvious gaps like current conditions, historical data, or radar imagery suggest the tool count is too low for comprehensive weather coverage.
The tool surface is severely incomplete for weather services. It lacks essential operations such as getting current conditions, historical weather data, radar maps, or air quality information. Agents will face significant limitations when trying to perform common weather-related tasks.