US 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_alertsC | Get weather alerts for a 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: one retrieves weather alerts for a state, while the other provides forecasts for a location. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool based on the user's request.
Both tools follow a consistent verb_noun pattern with 'get_' as the prefix, ensuring predictability and readability. The naming style is uniform across the toolset, with no deviations or mixed conventions.
With only two tools, the server feels thin for a weather domain, as it lacks essential operations like current conditions, historical data, or radar information. This minimal set may limit an agent's ability to handle comprehensive weather-related queries effectively.
The tool surface is significantly incomplete for a weather server, missing core functionalities such as current weather, radar maps, or severe weather details. While alerts and forecasts are useful, the absence of these key operations creates notable gaps that could lead to agent failures in broader scenarios.