A comprehensive system that provides intelligent weather services through orchestrated multi-agent architecture. Built for scalable agentic applications with and for easy deployment and interaction.
概览
A comprehensive system that provides intelligent weather services through orchestrated multi-agent architecture. Built for scalable agentic applications with and for easy deployment and interaction. - : ChatGPT-like interface at http://localhost:8501 - : Direct communication with weather agents - : System health monitoring and agent status - : Works on desktop, tablet, and mobile devices - : Proactive weather monitoring and personalized alerts - : Multi-source data aggregation and analysis - : Location-based weather planning and recommendations - : Centralized orchestration of all weather agents - : Weather server + Ollama LLM + Streamlit UI + Setup automation - : Production-ready microservices architecture - : Optimized Dockerfile with security best practices and health checks - : Full system startup with ./start-docker.
README
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Agentic MCP Weather Intelligence System 🌤️🤖
A comprehensive Agentic Model Context Protocol (MCP) system that provides intelligent weather services through orchestrated multi-agent architecture. Built for scalable agentic applications with full Docker support and Streamlit Web UI for easy deployment and interaction.
🌟 Key Features
🌐 Web Interface
- Streamlit Chat UI: ChatGPT-like interface at
http://localhost:8501 - Real-time Interactions: Direct communication with weather agents
- Visual Dashboard: System health monitoring and agent status
- Mobile Responsive: Works on desktop, tablet, and mobile devices
🤖 Multi-Agent Coordination
- Smart Alert Agent: Proactive weather monitoring and personalized alerts
- Weather Intelligence Agent: Multi-source data aggregation and analysis
- Travel Agent: Location-based weather planning and recommendations
- Agent Coordination Hub: Centralized orchestration of all weather agents
🐳 Docker-First Architecture
- Complete Containerization: Weather server + Ollama LLM + Streamlit UI + Setup automation
- Multi-Service Orchestration: Production-ready microservices architecture
- Production Ready: Optimized Dockerfile with security best practices and health checks
- One-Command Deployment: Full system startup with
./start-docker.sh
🔧 Modular Architecture
- Server Registry: Automatic discovery and management of MCP servers
- Agent Orchestrator: Intelligent workflow coordination with local LLM
- Multi-Agent Support: Extensible framework for specialized weather agents
- Health Monitoring: Real-time status tracking with comprehensive health endpoints
- API-First Design: RESTful APIs with interactive documentation at
/docs
🤖 Advanced Agentic Capabilities
- Natural Language Processing: Understand complex weather queries through LLM integration
- Intelligent Task Routing: Automatically delegate queries to specialized agents
- Multi-Location Coordination: Compare and analyze weather across multiple cities simultaneously
- Proactive Alert System: Smart monitoring with personalized notifications and thresholds
- Local LLM Integration: Ollama-powered reasoning and decision making
- Context-Aware Responses: Maintain conversation history and learning
🌐 Comprehensive Weather Services
- Real-Time Weather: Current conditions for any city worldwide via multiple APIs
- Advanced Forecasting: Detailed predictions using National Weather Service API
- Smart Alert System: Weather warnings, emergency notifications, and custom thresholds
- Multi-Source Intelligence: Data fusion from weather.gov, wttr.in, and additional sources
- Travel Planning: Location-based weather analysis for trip planning and recommendations
🏗️ System Architecture
┌─────────────────────────────────────────────────────────────────────────────┐安装
docker run -p 8000:8000 --env-file .env --add-host=host.docker.internal:host-gateway weather-mcp