This MCP connects a Python client with a weather data server, enabling users to query weather alerts and forecasts in natural language. It integrates Google's Gemini AI for interaction and communicates with the National Weather Service API to retrieve relevant weather information. Designed for ease of use, it supports natural language queries about US weather conditions, utilizing a model context protocol for seamless data exchange.
Added on:
Created by:
Apr 05 2025
This MCP connects a Python client with a weather data server, enabling users to query weather alerts and forecasts in natural language. It integrates Google's Gemini AI for interaction and communicates with the National Weather Service API to retrieve relevant weather information. Designed for ease of use, it supports natural language queries about US weather conditions, utilizing a model context protocol for seamless data exchange.
Added on:
Created by:
Apr 05 2025
Abhinav
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What is Weather Data MCP?
This MCP implements a weather information system that allows users to access real-time US weather data through a client-server architecture. It leverages the Model Context Protocol (MCP) to facilitate data exchange between a Python client and a weather data server. Users can ask natural language questions about weather alerts in specific states or detailed forecasts for locations specified by latitude and longitude. The server communicates with the National Weather Service API to fetch accurate and up-to-date weather alerts and forecasts. Powered by Google's Gemini AI, it interprets user queries effectively, providing relevant weather information efficiently, making it ideal for weather enthusiasts, developers, and data analysts.
Who will use Weather Data MCP?
- Weather app developers
- Data analysts
- Weather enthusiasts
- Researchers
- Educational institutions
How to use the Weather Data MCP?
- Step1: Clone the repository from GitHub
- Step2: Install the required dependencies using pip or uv
- Step3: Create a '.env' file with your Gemini API key in the root directory
- Step4: Run the server.py script to start the weather data server
- Step5: Run the client.py script to connect and interact with the server
- Step6: Ask weather-related questions in natural language, such as alerts or forecasts
Weather Data MCP's Core Features & Benefits
The Core Features
- get_alerts
- get_forecast
The Benefits
- Provides real-time weather alerts and forecasts
- Natural language interface for easy querying
- Seamless integration with national weather data sources
Weather Data MCP's Main Use Cases & Applications
- Weather alert notifications for US states
- Detailed weather forecasting for locations
- Educational demonstration of MCP architecture
- Weather data integration in applications
FAQs of Weather Data MCP
Developer
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