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MCP Server Client Example
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MCP Server Client Example

A Python-based MCP client and server example project, including a weather server implementation and a Claude AI interaction client. It requires an Anthropic API key to run.
Location servicesArtificial intelligence chatbots#MCP Protocol#Weather service#AI interaction#Python example.Python
2 points
13

What is MCP Weather Service?

This is a weather service system based on the Model Context Protocol (MCP), allowing developers to interact with weather data APIs and AI models (such as Claude) through a standardized protocol. The server side provides weather data interfaces, and the client side can integrate AI conversation capabilities.

How to use MCP Weather Service?

You can connect to the service through a simple Python client, which supports natural language queries for weather information. The AI assistant will automatically parse the request and return structured weather data.

Use cases

Suitable for applications that need to combine weather data with AI conversation capabilities, such as intelligent travel assistants, agricultural monitoring systems, or weather warning notification services.

Main features

Standardized MCP protocolAdopt the Model Context Protocol to achieve standardized communication between the client and the server
AI integrationBuilt-in support for the Claude AI model, which can handle natural language weather queries
National Meteorological Service dataConnect to the National Meteorological Service API to obtain authoritative weather data

Advantages and limitations

Advantages
Out-of-the-box Python implementation for quick deployment
AI-assisted natural language interaction experience
Modular design for easy expansion of new functions
Limitations
Requires a Python 3.12+ environment
Depends on the Anthropic API key
Currently only supports basic weather query functions

How to use

Environment preparation
Install Python 3.12 or a higher version. It is recommended to use uv to manage the environment.
Create a virtual environment
Use uv to create and activate a Python virtual environment.
Install dependencies
Use uv to install the dependencies required by the project.
Configure the API key
Copy the .env.example file to .env and fill in your Anthropic API key

Usage examples

Basic weather queryQuery the weather conditions of a specified city through natural language
Multi-day forecastGet the weather trend forecast for multiple days in the future

Frequently Asked Questions

How to obtain an Anthropic API key?
Which cities' weather queries are supported?
Can other AI models be extended?

Related resources

MCP Protocol official website
Official documentation for the Model Context Protocol
GitHub repository
Project source code repository
Anthropic API documentation
API usage guide for Claude AI
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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