Multi-Server Model Context Protocol (MCP) Demo

A complete demonstration of building and integrating multiple Model Context Protocol (MCP) servers with a LangGraph ReAct agent powered by Groq and real-time OpenWeatherMap data.

This project showcases how an LLM agent can dynamically discover and consume tools across different MCP servers and transport protocols (stdio and streamable-http) in a single unified workflow.

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🏗️ Architecture

flowchart LR
    subgraph Agent["LangGraph ReAct Agent (client.py)"]
        ChatGroq["LLM: Groq (Qwen / ChatGroq)"]
        MultiMCP["MultiServerMCPClient"]
    end

    subgraph MathServer["Math MCP Server (mathserver.py)"]
        MathTools["Tools: add, sub, mul, div"]
    end

    subgraph WeatherServer["Weather MCP Server (weatherserver.py)"]
        WeatherTools["Tool: get_weather (OpenWeatherMap API)"]
    end

    MultiMCP -- "stdio transport (subprocess)" --> MathServer
    MultiMCP -- "streamable-http (http://127.0.0.1:8000/mcp)" --> WeatherServer

Components

1. Math MCP Server ([mathserver.py](file:///c:/Users/SREESHANTH_K/Desktop/Mcp_demo/mathserver.py)):

   • Built with FastMCP.
   • Runs over stdio transport.
   • Exposes arithmetic tools: add, sub, mul, div.
   • Automatically launched as a background subprocess by the MCP client.

2. Weather MCP Server ([weatherserver.py](file:///c:/Users/SREESHANTH_K/Desktop/Mcp_demo/weatherserver.py)):

   • Built with FastMCP running over streamable-http transport at http://127.0.0.1:8000/mcp.
   • Uses httpx to fetch live meteorological data from the OpenWeatherMap API.
   • Exposes the get_weather tool (returns temperature, weather description, feels like, and humidity).

3. Orchestrator Client ([client.py](file:///c:/Users/SREESHANTH_K/Desktop/Mcp_demo/client.py)):

   • Connects to both MCP servers simultaneously using MultiServerMCPClient from langchain-mcp-adapters.
   • Assembles the tools and powers a LangGraph ReAct agent using Groq's fast LLM inference (ChatGroq).

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📁 Project Structure

Mcp_demo/
├── client.py           # ReAct Agent & Multi-Server MCP client orchestrator
├── mathserver.py       # FastMCP server running on stdio transport
├── weatherserver.py    # FastMCP server with OpenWeatherMap API on HTTP transport
├── requirements.txt    # Python package dependencies
├── pyproject.toml      # Project configuration & metadata
├── .env.example        # Environment variables template
├── .gitignore          # Git ignore rules (protects .env and caches)
└── README.md           # Project documentation

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🚀 Getting Started

1. Prerequisites

• Python 3.10+
• Groq API Key
• OpenWeatherMap API Key (free tier)

2. Installation

Clone the repository and install dependencies:

git clone https://github.com/sreeshanthkprakash-stack/MCP-Server.git
cd MCP-Server

# Create and activate virtual environment
python -m venv .venv
# On Windows:
.venv\Scripts\activate
# On Linux/macOS:
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

3. Environment Configuration

Create a .env file in the root directory (or copy from [.env.example](file:///c:/Users/SREESHANTH_K/Desktop/Mcp_demo/.env.example)):

GROQ_API_KEY=your_groq_api_key_here
OPENWEATHER_API_KEY=your_openweather_api_key_here

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🧪 Running the Application

Step 1: Start the Weather MCP Server

Since the weather server communicates over HTTP, start it first in a terminal:

python weatherserver.py

The weather server will start listening at http://127.0.0.1:8000/mcp.

Step 2: Run the Agent Client

Open a second terminal window (ensure your virtual environment is active), and run:

python client.py

Expected Output Example

math_response The result of the expression ((15*20)+200)/4 is 125.
weather_response Weather in Hyderabad: haze, temperature 29.5°C (feels like 32.1°C), humidity 65%

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📦 Dependencies

• mcp: Official Model Context Protocol SDK (FastMCP)
• langchain-mcp-adapters: Connects LangChain to MCP servers
• langgraph: Graph-based agent orchestration runtime
• langchain-groq: High-speed LLM inference with Groq
• httpx: Async HTTP client for weather API requests
• python-dotenv: Secure environment variable loading

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📄 License

This project is open-source and available under the MIT License.