MCP-Weather Server

by aaasoulmate

MCP-Augmented LLM for Reaching Weather Information

Overview

This system enhances Large Language Models (LLMs) with weather data capabilities using the Model Context Protocol (MCP) framework.

Demo

Components

  • MCP Client: Store LLms
  • MCP Server: Intermediate agent connecting external tools / resources

Configuration

DeepSeek Platform

BASE_URL=https://api.deepseek.com MODEL=deepseek-chat OPENAI_API_KEY=<your_api_key_here>

OpenWeather Platform

OPENWEATHER_API_BASE=https://api.openweathermap.org/data/2.5/weather USER_AGENT=weather-app/1.0 API_KEY=<your_openweather_api_key>

Installation & Execution

  1. Initialize project:
uv init weather_mcp cd weather_mcp

where weather_mcp is the project file name.

  1. Install dependencies:
uv add mcp httpx
  1. Launch system:
cd ./utils python client.py server.py

Note: Replace all <your_api_key_here> placeholders with actual API keys

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security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

An intermediate agent server that enhances LLMs with weather data capabilities using the Model Context Protocol (MCP) framework, enabling retrieval of real-time weather information.

  1. Overview
    1. Demo
      1. Components
    2. Configuration
      1. DeepSeek Platform
      2. OpenWeather Platform
    3. Installation & Execution

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