analytics-data

Caiyun Weather

by marcusbai

Get real-time weather data and forecasts with Caiyun Weather API, ideal for travel planning and outdoor activities using

Integrates with Caiyun Weather API to provide real-time weather data and forecasts based on geographic coordinates or location names for travel planning and outdoor activities.

github stars

9

Built-in coordinates for 35 major Chinese citiesMinute-level precipitation forecastsSupports Chinese and English languages

best for

  • / Travel planning and outdoor activity preparation
  • / Weather monitoring for Chinese locations
  • / Applications needing detailed precipitation forecasts
  • / Air quality analysis and tracking

capabilities

  • / Get current weather conditions (temperature, humidity, wind, pressure)
  • / Retrieve hourly forecasts for next 24+ hours
  • / Access daily weather forecasts for multiple days
  • / Check minute-by-minute precipitation for next 2 hours
  • / Get weather alerts and warnings
  • / Query air quality trends and pollution data

what it does

Provides real-time weather data and forecasts from Caiyun Weather API using geographic coordinates or location names.

about

Caiyun Weather is a community-built MCP server published by marcusbai that provides AI assistants with tools and capabilities via the Model Context Protocol. Get real-time weather data and forecasts with Caiyun Weather API, ideal for travel planning and outdoor activities using It is categorized under analytics data.

how to install

You can install Caiyun Weather in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Caiyun Weather is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

彩云天气 MCP 服务器

smithery badge

基于彩云天气 API 的 Model Context Protocol (MCP) 服务器,提供天气数据查询功能。

功能特点

  • 实时天气数据:温度、湿度、风速、气压、能见度等
  • 分钟级降水预报:未来2小时的降水情况
  • 小时级天气预报:未来24小时或更长时间的天气预报
  • 每日天气预报:未来多天的天气预报
  • 天气预警信息:各类天气预警
  • 空气质量趋势:24小时空气质量变化趋势和主要污染物分析
  • 详细生活指数:运动、旅行、洗车、穿衣等详细生活建议
  • 降水类型识别:区分雨、雪、雨夹雪、冰雹等降水类型
  • 地址查询:支持通过地址查询天气,内置35个主要城市坐标缓存,无需额外配置即可使用
  • 多语言支持:支持中文和英文
  • 单位制选择:支持公制和英制

安装

安装 Smithery

通过 Smithery 安装 彩云天气 对于Claude的桌面应用:

npm install @smithery/cli -g
smithery install @pepperai/caiyun-weather-mcp

通过 NPX 使用

您可以直接通过 NPX 运行:

npx caiyun-weather-mcp --api-key=您的彩云天气API密钥

或者设置环境变量:

CAIYUN_API_KEY=您的密钥 npx caiyun-weather-mcp

从源码安装

  1. 克隆仓库:
git clone https://github.com/marcusbai/caiyun-weather-mcp.git
cd caiyun-weather-mcp
  1. 安装依赖:
npm install

注意:本项目依赖于 Model Context Protocol (MCP) SDK,该SDK需要在运行环境中可用。MCP SDK通常由Claude或其他支持MCP的应用程序提供。

  1. 构建项目:
npm run build

配置

在使用前,需要配置彩云天气API密钥。地址查询功能支持内置城市缓存,高德地图API密钥为推荐配置。

彩云天气API密钥

  1. 访问 彩云天气开发者中心
  2. 注册并登录账号
  3. 创建应用并获取API密钥

高德地图API密钥(推荐)

  1. 访问 高德开放平台
  2. 注册并登录账号
  3. 创建应用并获取API密钥,需要启用"地理编码"服务

💡 提示:高德地图API密钥为推荐配置。系统内置了35个主要城市的坐标缓存,包括所有直辖市、省会城市和经济发达城市,无需额外配置即可使用。

地址解析功能

支持的城市

系统内置了以下35个主要城市的坐标缓存:

直辖市:北京、上海、天津、重庆

省会及主要城市:广州、深圳、杭州、南京、武汉、成都、西安、长沙、沈阳、大连、青岛、厦门、苏州、郑州、济南、哈尔滨、石家庄、太原、合肥、南昌、福州、南宁、昆明、贵阳、兰州、西宁、拉萨、呼和浩特、海口、银川、乌鲁木齐

智能地址匹配

支持多种地址格式和智能匹配:

  • 标准格式上海上海市
  • 详细地址上海市浦东新区北京市朝阳区
  • 城市别名魔都→上海、帝都→北京、羊城→广州、鹏城→深圳等

地址解析策略

  1. 缓存优先:内置城市坐标立即返回
  2. API增强:配置高德API后支持任意地址
  3. 降级处理:未知地址返回北京坐标并提示配置

配置MCP设置

编辑MCP设置文件,添加彩云天气MCP服务器配置:

{
  "mcpServers": {
    "caiyun-weather": {
      "command": "node",
      "args": ["完整路径/caiyun-weather-mcp/dist/index.js"],
      "env": {
        "CAIYUN_API_KEY": "您的彩云天气API密钥",
        "AMAP_API_KEY": "您的高德地图API密钥(推荐)"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

如果您通过 NPX 安装了本服务,可以使用以下配置:

{
  "mcpServers": {
    "caiyun-weather": {
      "command": "npx",
      "args": ["caiyun-weather-mcp"],
      "env": {
        "CAIYUN_API_KEY": "您的彩云天气API密钥",
        "AMAP_API_KEY": "您的高德地图API密钥(推荐)"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

使用示例

根据经纬度获取天气信息

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_weather_by_location</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "daily_steps": 5,
  "hourly_steps": 24,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

根据地址获取天气信息

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_weather_by_address</tool_name>
<arguments>
{
  "address": "上海市",
  "daily_steps": 5,
  "hourly_steps": 24,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取实时天气数据

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_realtime_weather</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取分钟级降水预报

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_minutely_forecast</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取小时级天气预报

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_hourly_forecast</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "hourly_steps": 24,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取每日天气预报

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_daily_forecast</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "daily_steps": 5,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取天气预警信息

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_weather_alert</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取空气质量趋势

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_air_quality_trend</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

获取详细生活指数

<use_mcp_tool>
<server_name>caiyun-weather</server_name>
<tool_name>get_detailed_life_index</tool_name>
<arguments>
{
  "longitude": 116.3976,
  "latitude": 39.9075,
  "language": "zh_CN",
  "unit": "metric"
}
</arguments>
</use_mcp_tool>

参数说明

通用参数

  • longitude:经度
  • latitude:纬度
  • address:地址(仅用于 get_weather_by_address
  • daily_steps:每日预报天数(1-15,默认5)
  • hourly_steps:小时预报数量(1-360,默认24)
  • language:语言(zh_CNen_US,默认 zh_CN
  • unit:单位制(metricimperial,默认 metric

许可证

MIT

FAQ

What is the Caiyun Weather MCP server?
Caiyun Weather is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Caiyun Weather?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Caiyun Weather is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Caiyun Weather against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Caiyun Weather is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Caiyun Weather reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Caiyun Weather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Caiyun Weather surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Caiyun Weather has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Caiyun Weather benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Caiyun Weather into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Caiyun Weather is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.