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MCP-Weather Server

by aaasoulmate
GitHub
Python
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LLM ampliado con MCP para acceder a información meteorológica

Descripción general

Este sistema mejora los modelos de lenguaje grande (LLM) con capacidades de datos meteorológicos utilizando el marco del Protocolo de contexto de modelo (MCP).

Manifestación

Una demostración

Componentes

  • Cliente MCP : Almacenar LLms
  • Servidor MCP : agente intermedio que conecta herramientas/recursos externos

Configuración

Plataforma DeepSeek

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

Plataforma OpenWeather

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

Instalación y ejecución

  1. Inicializar proyecto:
uv init weather_mcp cd weather_mcp

donde weather_mcp es el nombre del archivo del proyecto.

  1. Instalar dependencias:
uv add mcp httpx
  1. Sistema de lanzamiento:
cd ./utils python client.py server.py

Nota: Reemplace todos los marcadores de posición <your_api_key_here> con claves API reales

This server cannot be installed

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

How are these scores calculated?

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.

Un servidor de agente intermedio que mejora los LLM con capacidades de datos meteorológicos utilizando el marco del Protocolo de Contexto de Modelo (MCP), lo que permite la recuperación de información meteorológica en tiempo real.

  1. Descripción general
    1. Manifestación
      1. Componentes
    2. Configuración
      1. Plataforma DeepSeek
      2. Plataforma OpenWeather
    3. Instalación y ejecución

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