Weather and Math

MCP Server and client demo (POC)

python

0

GitHub Stars

python

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "durgeshmca-mcpserverpocdemo": {
      "command": "python",
      "args": [
        "weather_server.py"
      ],
      "env": {
        "GROQ_API_KEY": "YOUR_GROQ_API_KEY"
      }
    }
  }
}

You will run a local MCP server setup that demonstrates a multi-tool AI assistant. It connects tools through the Model Context Protocol (MCP), uses LangChain adapters, and simulates a weather API alongside a math tool. This architecture lets you compose intelligent interactions where an AI agent can leverage separate local tools to compute results and fetch data in a seamless chat experience.

How to use

You interact with an AI agent that can call the integrated MCP tools. Start the weather server, then run the client. The agent will use the math tool for calculations and the weather tool for weather data, providing answers that combine computation and data retrieval.

Typical usage flows include asking for mathematical results, like arithmetic expressions, and querying simulated weather for a city. The agent detects tool usage and returns step-by-step results when applicable, presenting a natural conversational experience.

Documentation & install

Installation

How to use

Available tools

weather

math