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juhemcp

Juhe Weather MCP Server

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by juhemcp
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Python
Remote

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]:

Related MCP server: HeFeng Weather MCP Server

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

"mcpServers": {
  "jweather-mcp-server": {
    "command": "uvx",
    "args": [
      "jweather-mcp-server"
    ],
    "env": {
      "JUHE_WEATHER_API_KEY": "your_api_key"
    }
  }
}
"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

  1. "查询下苏州的天气"

  2. "今天上海的天气如何？"

Available Tools

1 tool
query_weatherC

根据城市、地区、区县名称查询当地实时天气预报情况

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYes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

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions '实时' (real-time) which indicates freshness of data, but doesn't disclose important behavioral traits like rate limits, authentication requirements, error handling, or what happens when invalid city names are provided. The description is insufficient for a mutation-free query tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient Chinese sentence that gets straight to the point. It's appropriately sized for a simple query tool with one parameter. No wasted words or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a query tool with no annotations and no output schema, the description is incomplete. It doesn't explain what information the weather forecast includes (temperature, precipitation, etc.), the format of returned data, or any limitations. The agent would need to guess about the response structure and content.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the single parameter 'city' well-documented in the schema. The description adds minimal value beyond the schema, only reinforcing that queries are based on city/region/county names. With high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: querying real-time weather forecasts based on city/region/county names. It specifies the verb ('查询' - query) and resource ('天气预报情况' - weather forecast situation). However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, constraints, or comparison with other weather-related tools. The absence of sibling tools doesn't excuse the lack of usage context for the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedquery_weather
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TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'query_weather' has a clear and distinct purpose of querying real-time weather forecasts based on location names.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'query_weather' follows a clear verb_noun pattern, which would be consistent if more tools were added.

Tool Count2/5

A single tool is too few for a weather server's apparent scope, which typically involves forecasts, historical data, alerts, or multiple query types. This minimal set feels thin and limits functionality for agents.

Completeness2/5

The tool surface is severely incomplete for a weather domain. It only provides real-time queries, with obvious gaps like no support for forecasts (e.g., hourly, daily), historical data, weather alerts, or location-based searches beyond basic queries.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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Related MCP Connectors

Related MCP Servers

  • Caiyun Weather MCP Server

    marcusbai
    F
    license
    B
    quality
    D
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    A Model Context Protocol server that provides comprehensive weather data querying capabilities based on the Caiyun Weather API, supporting real-time weather, forecasts, and alerts with multi-language support.
    7
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  • mcp-weather

    githubmilind
    F
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    A Model Context Protocol (MCP) server that enables AI assistants and LLMs to access real-time weather data and forecasts by connecting to the OpenWeatherMap API.
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