Caiyun Weather MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AMAP_API_KEY | No | Your Amap (Gaode Maps) API key (optional for address lookup functionality) | |
| CAIYUN_API_KEY | Yes | Your Caiyun Weather API key |
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_weather_by_locationC | 根据经纬度获取天气信息 |
| get_weather_by_addressC | 根据地址获取天气信息 |
| get_realtime_weatherC | 获取实时天气数据 |
| get_minutely_forecastC | 获取分钟级降水预报 |
| get_hourly_forecastC | 获取小时级天气预报 |
| get_daily_forecastC | 获取天级天气预报 |
| get_weather_alertC | 获取天气预警信息 |
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 7 tools
Each tool has a clearly distinct purpose with no overlap: daily, hourly, and minutely forecasts target different time granularities, realtime weather provides current conditions, weather alerts are separate, and the last two tools differ by input type (address vs. location). An agent can easily tell them apart based on their specific functions.
All tool names follow a consistent verb_noun pattern using 'get_' as the prefix, followed by descriptive nouns like 'daily_forecast' or 'weather_by_address'. There are no deviations in style or convention, making the naming predictable and easy to understand.
With 7 tools, this server is well-scoped for a weather domain, covering key aspects like forecasts, real-time data, alerts, and location-based queries. Each tool earns its place without being excessive or insufficient, aligning perfectly with typical MCP server expectations.
The tool set is highly complete for weather data retrieval, covering forecasts, real-time info, alerts, and multiple input methods. A minor gap might be the lack of historical weather data or more advanced queries, but core workflows are fully supported, allowing agents to handle most weather-related tasks effectively.