by marcusbai
Get real-time weather data and forecasts with Caiyun Weather API, ideal for travel planning and outdoor activities using
Provides real-time weather data and forecasts from Caiyun Weather API using geographic coordinates or location names.
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.
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.
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.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Caiyun Weather benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: Caiyun Weather surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend Caiyun Weather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
I recommend Caiyun Weather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Useful MCP listing: Caiyun Weather is the kind of server we cite when onboarding engineers to host + tool permissions.
Strong directory entry: Caiyun Weather surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Caiyun Weather is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend Caiyun Weather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired Caiyun Weather into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Caiyun Weather benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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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。
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
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
git clone https://github.com/marcusbai/caiyun-weather-mcp.git
cd caiyun-weather-mcp
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。
npm run build
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。
💡 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。
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
支持多种地址格式和智能匹配：
上海、上海市上海市浦东新区、北京市朝阳区魔都→上海、帝都→北京、羊城→广州、鹏城→深圳等编辑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": []
}
}
}
<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>
<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>
<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>
<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>
<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>
<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>
<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>
<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>
<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>
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_CN 或 en_US，默认 zh_CN）unit：单位制（metric 或 imperial，默认 metric）MIT
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.