mcp_server_deployement

sherwaldeepesh/mcp_server_deployement

3.1

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The Model Context Protocol (MCP) server is designed to facilitate efficient communication between clients and servers, supporting scalable and robust interactions.

MCP Server Deployment Application

Description

This project explores the Model Context Protocol (MCP), its architecture, and practical implementation. The journey includes building an MCP client and server, integrating chatbot functionality, and incorporating prompt and resource features. It also includes experimentation with Claude desktop services and the final deployment of remote servers using robust communication methods.

We initially implemented server communication using stdio for simplicity, then upgraded to Server-Sent Events (SSE) to support production-ready performance and scalability.

Features

  • Designed and implemented MCP client-server architecture
  • Integrated MCP chatbot with prompt and resource extensions
  • Utilized Claude desktop services for local interaction
  • Remote server creation and deployment workflow
  • Migration from stdio to SSE for scalable deployment

Installation

  1. Clone the repository:

    git clone https://github.com/sherwaldeepesh/mcp_server_deployement.git
    cd mcp-server-deployment
    
  2. (Optional) Set up a virtual environment:

    python -m venv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
    
  3. Install required dependencies:

    pip install -r requirements.txt
    

Usage

  1. Launch the MCP server:

    python mcp_server.py
    
  2. Start the MCP client to connect and interact with the server:

    python mcp_client.py
    
  3. Explore added chatbot and resource features by navigating through the CLI or web interface.

Note: Update this section with exact usage examples once the application interfaces are finalized. [Needs to update.]

Technologies Used

  • Python
  • Model Context Protocol (MCP)
  • Server-Sent Events (SSE)
  • Claude Desktop Services
  • CLI / Jupyter (if applicable)
  • Shell scripting (for deployment steps)