MCP Weather Project
An MCP server that provides real-time weather alerts for US states using the National Weather Service (NWS) API. It also includes utility features for message echoing and generating customizable greeting prompts.
README
MCP Weather Project
A Model Context Protocol (MCP) server implementation that provides weather alerts via the National Weather Service (NWS) API. This project includes both a FastMCP server and a LangChain-based client with memory capabilities.
Features
- Weather Alerts: Fetch active weather alerts for any US state using the NWS API.
- Echo Resource: A simple resource that echoes back messages.
- Greeting Prompt: A customizable greeting prompt generator.
- Interactive Client: A CLI-based chat client powered by Groq's Llama 3.3 model with conversation memory.
Prerequisites
Installation
-
Clone the repository:
git clone <repository_url> cd mcpfile -
Install dependencies: Using
uv(recommended):uv syncOr using pip:
pip install -r requirements.txt(Note: You may need to generate a
requirements.txtfrompyproject.tomlif not usinguv) -
Set up Environment Variables: Create a
.envfile in the root directory and add your Groq API key:GROQ_API_KEY=your_groq_api_key_here
Usage
Running the Entry Point
The main.py is a simple entry point script that prints a welcome message.
uv run main.py
# OR
python main.py
Running the interactive Client
The client connects to the weather server and allows you to interact with it using natural language.
-
Ensure the server configuration in
server/weather.jsonis correct (it points toserver/weather.py). -
Run the client:
uv run server/client.py # OR if using a virtual environment directly: # python server/client.py -
Example Interaction:
You: Check weather alerts for TX Assistant: Checking weather alerts for Texas... [Agent responds with alerts]
Running the MCP Server Standalone
You can run the MCP server directly using uv. This is useful for inspection or debugging with the MCP Inspector.
uv run --with mcp[cli] mcp run server/weather.py
Configuration Verification
Ensure that server/weather.json points to the correct absolute path of your server/weather.py file.
{
"mcpServers": {
"weather": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"/your/absolute/path/to/mcp/mcpfile/server/weather.py"
]
}
}
}
Project Structure
server/weather.py: The main MCP server implementation usingFastMCP. Defines tools (get_alerts), resources, and prompts.server/client.py: An MCP client implementation usingLangChainandChatGroq. Handles the interactive chat session.server/weather.json: Configuration file for the MCP client to locate the server.main.py: Simple entry point script.pyproject.toml: Project configuration and dependencies.
Tools Available
get_alerts(state: str): Get active weather alerts for a US state (e.g., "CA", "NY").
Resources
echo://{message}: Echoes a message.
Prompts
greet_user(name: str, style: str): Generates a greeting in a specified style ("friendly", "formal", or "casual").
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。