Starter 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, and the other retrieves 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.
Both tools follow a consistent verb_noun pattern with 'get' as the verb, but they use kebab-case (get-alerts, get-forecast) instead of the more common snake_case. This minor deviation is still readable and predictable, though not perfectly aligned with typical conventions.
With only 2 tools, the server feels thin for a weather domain that could include more operations like historical data, radar images, or air quality. While it covers basic alerts and forecasts, the scope is limited and may not support comprehensive agent workflows.
The tool set is severely incomplete for a weather server, lacking essential operations such as current conditions, historical data, or multi-day forecasts. Agents will face dead ends when trying to perform common weather-related tasks beyond the two provided tools.