MCP Demo
What is MCP Demo Server?
The MCP Demo Server is a practical implementation of the Model Context Protocol that connects language models with external tools. This specific demo provides weather forecasting capabilities by integrating with the National Weather Service API.How to use the MCP Demo Server?
You can interact with the server through a simple client interface that sends natural language queries about weather conditions. The system will automatically determine the appropriate weather data to retrieve and present it in an easy-to-understand format.Use Cases
Ideal for checking current weather conditions, planning outdoor activities, or integrating weather data into other applications through natural language queries.Key Features
Weather ForecastProvides detailed weather forecasts including temperature, wind conditions, and sky conditions for locations worldwide
Weather AlertsCan check for active weather alerts and warnings in specified locations
Natural Language InterfaceUnderstands and responds to natural language queries about weather conditions
Pros and Cons
Advantages
Easy-to-use natural language interface
Provides comprehensive weather information from reliable sources
Can handle complex queries about weather conditions
Quick response time for weather data
Limitations
Limited to weather-related queries only
Requires an API key for DeepSeek integration
Accuracy depends on the underlying weather data sources
Currently only supports English queries
Getting Started
Set up your environment
Install the required dependencies and create a virtual environment
Install required packages
Add the necessary Python packages including MCP and its dependencies
Configure API key
Add your DeepSeek API key to the .env file
Run the client
Start interacting with the weather service through the client interface
Example Queries
Basic Weather QueryGetting the current weather forecast for a major city
Multi-day ForecastRequesting weather information for multiple days
Weather Alerts CheckChecking for severe weather alerts
Frequently Asked Questions
What weather data sources does this use?
Do I need a DeepSeek API key?
Can I use this with other LLMs besides DeepSeek?
What locations are supported?
How accurate is the weather data?
Additional Resources
MCP Documentation
Official documentation for Model Context Protocol
National Weather Service API
Documentation for the weather data API used by this demo
DeepSeek API
Information about the DeepSeek language model API
Example Repository
Source code for this demonstration project
精選MCP服務推薦

Markdownify MCP
Markdownify是一個多功能文件轉換服務,支持將PDF、圖片、音頻等多種格式及網頁內容轉換為Markdown格式。
TypeScript
1.7K
5分

Baidu Map
已認證
百度地圖MCP Server是國內首個兼容MCP協議的地圖服務,提供地理編碼、路線規劃等10個標準化API接口,支持Python和Typescript快速接入,賦能智能體實現地圖相關功能。
Python
697
4.5分

Firecrawl MCP Server
Firecrawl MCP Server是一個集成Firecrawl網頁抓取能力的模型上下文協議服務器,提供豐富的網頁抓取、搜索和內容提取功能。
TypeScript
3.8K
5分

Sequential Thinking MCP Server
一個基於MCP協議的結構化思維服務器,通過定義思考階段幫助分解複雜問題並生成總結
Python
249
4.5分

Context7
Context7 MCP是一個為AI編程助手提供即時、版本特定文檔和代碼示例的服務,通過Model Context Protocol直接集成到提示中,解決LLM使用過時信息的問題。
TypeScript
5.2K
4.7分

Notion Api MCP
已認證
一個基於Python的MCP服務器,通過Notion API提供高級待辦事項管理和內容組織功能,實現AI模型與Notion的無縫集成。
Python
113
4.5分

Edgeone Pages MCP Server
EdgeOne Pages MCP是一個通過MCP協議快速部署HTML內容到EdgeOne Pages並獲取公開URL的服務
TypeScript
246
4.8分

Magic MCP
Magic Component Platform (MCP) 是一個AI驅動的UI組件生成工具,通過自然語言描述幫助開發者快速創建現代化UI組件,支持多種IDE集成。
JavaScript
1.7K
5分