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 in functionality, making it easy for an agent to choose the correct tool based on the need for alerts versus general weather predictions.
Both tools follow a consistent verb_noun naming pattern with hyphens (get-alerts and get-forecast). This uniformity makes the tool set predictable and easy to understand, adhering to a clear convention throughout.
With only 2 tools, the server feels thin for a weather domain, lacking essential operations like current conditions, historical data, or radar imagery. While the tools are well-defined, the count is too low to adequately cover typical weather-related use cases, suggesting an incomplete surface.
The tool set is severely incomplete for a weather server, missing core functionalities such as current weather conditions, historical data, or severe weather details. Agents will face significant gaps when trying to perform common weather-related tasks, leading to potential failures in broader workflows.