mcp-swedish-weather
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| current_weatherB | Get current weather for a location in Sweden using SMHI. |
| weather_forecastA | Get hourly weather forecast for a location in Sweden using SMHI. |
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 provides current weather data, while the other provides forecast data. There is no overlap or ambiguity between them, as each targets a specific temporal aspect of weather information.
Both tools follow a consistent naming pattern with a descriptive adjective_noun structure (current_weather, weather_forecast). The naming is uniform and predictable, making it easy to understand their functions at a glance.
With only two tools, the server feels thin for a weather domain that typically requires more comprehensive coverage, such as historical data, alerts, or location search. While the tools cover current and forecast data, the scope is limited and may not support complex agent workflows effectively.
The toolset is significantly incomplete for a weather server, lacking essential operations like historical weather data, location search/autocomplete, weather alerts, or multi-day forecasts. This creates gaps that could lead to agent failures when handling broader weather-related queries.