Weather Checker
Enables real-time weather lookup for any location via MCP, returning concise summaries from wttr.in.
README
⛅ Weather MCP Server
A lightweight MCP (Model Context Protocol) server that exposes a single tool — real-time weather lookup for any location — to any MCP-compatible client, such as Claude Desktop.
🧠 How It Works
- A
FastMCPserver named "Weather Checker" is started over stdio transport. - It exposes one async tool,
check_weather(location: str), callable by any connected MCP client. - Internally, the tool calls
get_weather(), which hits wttr.in — a free, no-auth-required weather service — and returns a concise, one-line weather summary for the given location. - No API keys, no sign-ups, no external dependencies beyond the
mcppackage itself.
🗂️ Project Structure
├── main.py # MCP server entry point — defines and runs the check_weather tool
├── tools/
│ ├── __init__.py
│ └── weather.py # Fetches weather data from wttr.in
├── pyproject.toml # Project metadata and dependencies (uv-managed)
├── requrements.txt # Pip-installable dependencies
├── uv.lock # Locked dependency versions
└── .python-version # Python 3.13
🛠️ Tech Stack
| Layer | Technology |
|---|---|
| Protocol | MCP (Model Context Protocol) — FastMCP, stdio transport |
| Weather Data Source | wttr.in — free console-friendly weather API |
| HTTP Client | Python standard library (urllib.request) |
| Package Management | uv |
| Language | Python 3.13 |
⚙️ Local Setup
1. Clone the Repository
git clone https://github.com/<your-username>/<repo-name>.git
cd <repo-name>
2. Install Dependencies
Using uv (recommended, matches uv.lock):
uv sync
Or using standard venv + pip:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -e .
3. Run the Server
python main.py
The server starts and communicates over stdio — it's designed to be launched by an MCP client, not accessed directly via a browser or REST call.
🔌 Connecting to an MCP Client
To use this server with an MCP-compatible client (e.g. Claude Desktop), add it to the client's MCP server configuration:
{
"mcpServers": {
"weather-checker": {
"command": "python",
"args": ["main.py"]
}
}
}
If using uv:
{
"mcpServers": {
"weather-checker": {
"command": "uv",
"args": ["run", "main.py"]
}
}
}
Once connected, the client can call the check_weather tool directly — for example, asking "What's the weather in London?" will invoke check_weather(location="London") behind the scenes.
🔧 Available Tools
| Tool | Parameters | Returns | Description |
|---|---|---|---|
check_weather |
location: str (e.g. "New York", "London") |
Concise weather summary (string) | Fetches current weather conditions for the specified location via wttr.in |
Example Output
New York: ☀️ +24°C
📌 Key Features
- ✅ Zero-configuration — no API keys or environment variables required
- ✅ Minimal dependency footprint (
mcp[cli]only) - ✅ Clean separation between MCP tool definition (
main.py) and the underlying data-fetch logic (tools/weather.py) - ✅ Graceful error handling — returns a readable error string instead of raising on failed requests
- ✅ Async tool definition, ready to scale to additional tools in the same server
📄 License
This project is for educational purposes.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。