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
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 |
|---|---|
| get_weatherB | 특정 도시의 현재 날씨 정보를 가져옵니다. Args: city: 도시 이름 (서울, 부산, 인천, 대구, 대전, 광주, 울산, 제주 중 선택) Returns: 날씨 정보 문자열 |
| list_citiesB | 사용 가능한 도시 목록을 반환합니다. Returns: 사용 가능한 도시 목록 |
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_weather retrieves weather data for a specific city, while list_cities provides the list of available cities. There is no overlap or ambiguity between them.
Both tools follow a consistent verb_noun pattern (get_weather, list_cities) with clear, descriptive names that align with their functions. There are no deviations in naming style.
With only 2 tools, the server feels thin for a weather domain. It lacks essential operations like forecast retrieval, historical data, or location-based searches, which limits its utility for comprehensive weather-related tasks.
The tool set is severely incomplete for a weather server. It only supports current weather for a limited set of cities, missing forecasts, historical data, multi-city queries, and other common weather API features, leading to significant gaps in functionality.