Weather MCP Server

@pg-yuly

リポジトリ

基本情報

カテゴリ

メディアとデザイン

トランスポート

stdio

作者

pg-yuly

Weather MCP Server について

A weather information server built using Model Context Protocol (MCP) to provide real-time weather data and forecasts

Weather MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

Weather MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Weather MCP Server?

Weather MCP Server is a weather information server built using Model Context Protocol (MCP). It provides real-time weather data and forecasts for Chinese cities. It is designed for developers or users who need weather information accessible via MCP.

How to use Weather MCP Server?

Install dependencies with npm install, then start the server with npm start. The server exposes three APIs: query_weather (current conditions), query_forecast (daily forecasts), and query_hourly_forecast (hourly forecasts). Each API takes a city name as input.

Key features of Weather MCP Server?

Real-time weather information
Daily weather forecasts
Hourly weather forecasts
Detailed life indexes (clothing, makeup, cold prevention)

Use cases of Weather MCP Server?

Get current weather for a Chinese city.
Plan daily activities using forecast data.
Check hourly weather for short-term scheduling.
Use life indexes for outfit or health advice.

よくある質問

What cities does Weather MCP Server support?

It supports Chinese cities. The README does not list specific city names.

What data does Weather MCP Server provide?

It provides real-time weather, daily and hourly forecasts, and life indexes for clothing, makeup, and cold prevention.

How to install Weather MCP Server?

Use `npm install` to install the required dependencies.

How to start Weather MCP Server?

Run `npm start` to launch the server.

What APIs does Weather MCP Server offer?

`query_weather`, `query_forecast`, and `query_hourly_forecast`.

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