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juhemcp_jweather-mcp-server
Espejo dehttps: //github.com/juhemcp/jweather-mcp-server
3 years
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Juhe Weather MCP Server
一个提供全国天气预报查询功能的模型上下文协议(Model Context Protocol)服务器。该服务器使大型语言模型(LLMs)能够获取全国城市、地区的天气预报情况。
Components
Tools
服务器实现了一个工具:
- query_weather: 根据城市、地区、区县名称查询当地实时天气预报情况.
- 需要传入 "city"(城市、区县等名称)作为必须的字符串参数。
async def query_weather(
city: str = Field(description="查询的城市名称,如北京、上海、广州、深圳、泰顺等;城市或区县或地区名使用简写,严格按照规范填写,否则会导致查询失败")
) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
Install
This server requires Python 3.10 or higher. Install dependencies using uv (recommended) or pip
Using uv (recommended)
When using uv no specific installation is needed. We will use uvx to directly run jweather-mcp-server.
uvx jweather-mcp-server
Using PIP
Alternatively you can install jweather-mcp-server via pip:
pip install jweather-mcp-server
After installation, you can run it as a script using:
python -m jweather_mcp_server
Configuration
Environment Variables
JUHE_WEATHER_API_KEY
: 聚合数据的天气预报查询API密钥。获取:https://www.juhe.cn/docs/api/id/73
JUHE_WEATHER_API_KEY=your_api_key
Configure For CLINE
Using uvx
"mcpServers": {
"jweather-mcp-server": {
"command": "uvx",
"args": [
"jweather-mcp-server"
],
"env": {
"JUHE_WEATHER_API_KEY": "your_api_key"
}
}
}
Using pip installation
"mcpServers": {
"jweather-mcp-server": {
"command": "python",
"args": [
"-m",
"jmobile_location_mcp_server"
],
"env": {
"JUHE_WEATHER_API_KEY": "your_api_key"
}
}
}
Debugging
You can use the MCP inspector to debug the server. For uvx installations:
npx @modelcontextprotocol/inspector uvx jweather-mcp-server
Or if you've installed the package in a specific directory or are developing on it:
cd path/to/servers/src/jweather-mcp-server
npx @modelcontextprotocol/inspector uv run jweather-mcp-server
Examples of Questions for Cline
- "查询下苏州的天气"
- "今天上海的天气如何?"
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Reviews

user_fB1aQdrX
I have been using the juhemcp_jweather-mcp-server by MCP-Mirror and it’s fantastic! This server integrates seamlessly and provides accurate weather updates with minimal setup. The project on GitHub is well-documented and easy to navigate. It’s an essential tool for anyone looking to incorporate reliable weather data into their applications. Highly recommend!