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
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 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 weather alerts for a state, while get_forecast provides weather forecasts for a location. There is no overlap in functionality, making it easy for an agent to select the correct tool based on the need for alerts versus forecasts.
Both tools follow a consistent verb_noun pattern with 'get_' prefix and descriptive nouns (alerts, forecast). This uniformity enhances readability and predictability, making the tool set easy to navigate and understand.
With only 2 tools, the server feels under-scoped for a weather domain, which typically involves more operations like current conditions, historical data, or radar information. This limited set may restrict agent capabilities in handling comprehensive weather-related tasks.
The tool surface is significantly incomplete for a weather server, lacking essential operations such as getting current conditions, historical weather data, or radar imagery. This creates notable gaps that could lead to agent failures when trying to perform common weather-related workflows.