Weather-MCP
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| open_weather_forecast_israelA | Open a browser and navigate to the Israeli weather forecast website. |
| enter_weather_forecast_city_israelB | Type a city name into the search field on the Israeli forecast page. Args: city: The name of the city to search for (in Hebrew) |
| select_weather_forecast_city_israelB | Select the first city from the autocomplete suggestion list. |
| get_weather_forecast_content_israelA | Extract the weather forecast text from the currently open forecast page. Returns the cleaned textual content so the LLM can answer the user directly. |
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 4 tools
Each tool covers a distinct workflow step: opening the page, typing a city, selecting an autocomplete result, and extracting content. The main ambiguity is between open_weather_forecast_israel and get_weather_forecast_content_israel, since both could sound like they return forecast data without reading the descriptions carefully.
All tool names follow the same verb-first snake_case pattern and consistently include weather_forecast and israel context. This makes the order and purpose of the tools predictable.
Four tools is appropriate for the narrow browser-automation workflow this server provides. Each tool contributes one essential step, and the set is neither bloated nor too thin.
The tool surface covers the full workflow from opening the forecast site to retrieving the forecast text for a chosen city. It lacks fallback or reset tools, but those are not essential for the core task.