Servers With LLM Weather Live Info And Maths Tools
MCP server: Servers With LLM Weather Live Info And Maths Tools
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Multi-Server AI Agent with Math and Weather Tools
Project Overview
This project demonstrates a powerful AI agent built in Python that can perform multiple tasks by connecting to specialized micro-servers. The agent uses a Large Language Model (LLM) to understand user requests and intelligently delegates tasks to the correct server:
Math Server: A local server that handles arithmetic calculations (add, multiply, etc.).
Weather Server: A network server that connects to a live external API (WeatherAPI.com) to provide real-time weather information for any location.
This architecture showcases a modern, decoupled approach to building scalable and maintainable AI applications where different functionalities are handled by independent services.
Technologies & Tools Used Core Language:
Python: The foundation of the project.
AI & Agent Framework:
LangChain & LangGraph: Used to build the core agent logic, enabling it to reason and use tools in a step-by-step manner.
Groq: Provides the high-speed Large Language Model (LLM) that powers the agent's decision-making.
Server & Communication:
MCP (Multi-protocol Communication Platform): The framework used to create and manage the tool servers.
stdio & streamable-http: Two different communication protocols used by the servers to talk to the client.
httpx: A modern Python library used to make asynchronous API calls to the external weather service.
Configuration & Environment:
python-dotenv: For securely managing API keys and other secrets by loading them from a .env file.
