qweather-mcp
qweather-mcp
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QWeather API 用の MCP サーバー。モデル コンテキスト プロトコル (MCP) を通じて包括的な天気情報クエリ機能を提供します。
✨ 特徴
🌤️ リアルタイム天気予報
📅 複数日間の天気予報(3/7/10/15/30日間)
🔑 シンプルなAPIキー設定
🔌 カスタム API ベース URL のサポート
🛠️ 完全なツール統合
Related MCP server: OpenWeatherMap MCP Server
📦 インストール
スミザリー経由
推奨: Smitheryを使用して Claude Desktop に自動的にインストールします:
npx -y @smithery/cli install @overstarry/qweather-mcp --client claude手動設定
まず、 QWeather コンソールから API キーを取得します。
サーバーを起動します。
# stdio server
npx -y qweather-mcp環境変数を設定します。
QWEATHER_API_BASE=https://api.qweather.com
QWEATHER_API_KEY=<your-api-key>JSON構成
設定ファイルに以下を追加します:
{
"mcpServers": {
"qweather": {
"command": "npx",
"args": ["-y", "qweather-mcp"],
"env": {
"QWEATHER_API_BASE": "<your-api-url>",
"QWEATHER_API_KEY": "<your-api-key>"
}
}
}
}🛠️ 利用可能なツール
今すぐ天気予報
指定された場所の現在の天気情報を取得します。
天気予報を取得する
カスタマイズ可能な予報日で、指定した場所の天気予報情報を取得します。
3日間の天気予報
7日間予報
10日間予報
15日間の予報
30日間の予報
予測データには以下が含まれます:
温度範囲(最小/最大)
昼夜の天候
日の出/日の入り時刻
降水量
湿度
風の状態
UV指数
毎分降水量
今後 2 時間の降水量を分単位で予報します。
降水の種類(雨/雪)
1分あたりの降水量
正確な時間予測
リアルタイム予報の説明
時間ごとの予報を取得する
24 時間、72 時間、または 168 時間の 1 時間ごとの天気予報を提供します。
気温の変化
気象条件
風向と風力
相対湿度
大気圧
降水確率
雲量
天気予報を取得する
以下を含むリアルタイムの気象警報情報を提供します:
警告発令機関
警告レベルと種類
詳細な警告内容
警告の有効期間
関連する推奨事項
天気指数を取得する
さまざまなインデックス タイプをサポートする気象生命インデックス情報を提供します。
スポーツ指数
洗車指数
ドレッシング指数
釣り指数
UV指数
観光指数
アレルギー指数とその他16の生活指数
空気の質を知る
以下を含むリアルタイムの空気質データを提供します:
AQI指数
空気質レベル
一次汚染物質
健康アドバイス
汚染物質濃度
空気の質を1時間ごとに取得
今後 24 時間の空気質予報を 1 時間ごとに提供します。
1時間ごとのAQI予測
汚染物質濃度の変化
健康影響評価
保護に関する推奨事項
毎日の空気質情報
今後 3 日間の空気質予報を提供します。
毎日のAQI予測
一次汚染物質予測
空気質レベルの変化
健康保護に関するアドバイス
🤝 貢献する
問題や改善点のご意見をお待ちしております。貢献ガイドラインをご確認ください。
📄 ライセンス
マサチューセッツ工科大学
🔗 関連リンク
Available Tools
2 toolsget-weather-nowC
Get current weather for a location using QWeather API
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | Location ID for the city |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description implies a read operation but lacks details about API key requirements, error handling, or response format. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise single sentence. Could be improved by adding a hint about the sibling tool or output format without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity, the description is incomplete. It does not explain how to obtain the location ID or what the output contains, missing essential context for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter described as 'Location ID for the city'. The description adds no extra parameter info, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get current weather for a location' with a specific API mention. However, it does not differentiate from sibling 'lookup-city', which likely provides city IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention that the location parameter might come from the sibling tool 'lookup-city'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup-cityC
Look up city information by name
| Name | Required | Description | Default |
|---|---|---|---|
| cityName | Yes | Name of the city to look up |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description only states the basic action, with no mention of side effects, authentication needs, rate limits, or error handling (e.g., if city not found). This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action. It could be more structured (e.g., listing what information is returned), but it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter and no output schema, the description does not specify what fields of city information are returned, nor any behavioral context. This leaves the agent uncertain about the response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (single parameter well-described in schema). The description adds no extra meaning beyond 'by name', but the schema already provides a clear description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'look up city information by name', specifying verb and resource. However, it does not differentiate from the sibling tool 'get-weather-now', which may also involve city queries. The description lacks detail on what information is returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of prerequisites, limitations, or cases to avoid. The sibling tool exists but is not differentiated.
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.
2 tool updates
v1.0.0- First observed
get-weather-now - First observed
lookup-city
TDQS
Scored across 2 tools
The two tools serve clearly distinct purposes: one retrieves current weather data, and the other looks up city information. There is no overlap or ambiguity.
Both tools follow a consistent verb_noun pattern using snake_case: get-weather-now and lookup-city. The naming is predictable and clear.
With only 2 tools, the set is on the lower end of reasonable. While it covers the basics, it feels minimal for a weather API, which typically includes more operations like forecasts or alerts.
The tool set lacks essential weather features such as forecasts, historical data, or severe weather alerts. For a weather-focused server, the absence of these common operations is a notable gap.
Maintenance
Related MCP Connectors
OpenWeather MCP — wraps the OpenWeatherMap API (openweathermap.org)
Hosted MCP server for Xweather weather data: conditions, forecasts, alerts, and more.
Smarter Weather MCP: forecasts, alerts, outlooks, observations, AQI, grids, and map imagery.
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