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MCPFromScratch: Building a Model Context Protocol Server from Scratch

Welcome to MCPFromScratch - a comprehensive educational project that demonstrates how to build a complete client-server application using the Model Context Protocol (MCP) from the ground up.

🎯 What This Project Teaches

This repository is designed to help you understand:

  • Client-Server Architecture: How intelligent agents communicate with service providers
  • Model Context Protocol (MCP): A custom protocol for AI agents to discover and use server capabilities
  • Modern Python Web Development: Using FastAPI, WebSockets, and async/await patterns
  • AI Integration: How to build agents that leverage Large Language Models (LLMs)
  • Real-time Communication: WebSocket-based persistent connections for dynamic interactions

🏗️ Project Structure

The project consists of two main components:

  • Server (MCPFromScratch/server/): A FastAPI-based server that provides tools, prompts, and resources
  • Client (MCPFromScratch/client/): An intelligent agent that connects to the server and processes user queries

📚 Get Started with the Interactive Guide

👉 For the complete learning experience, open notebook.ipynb

The notebook provides:

  • Step-by-step explanations of all concepts
  • Detailed code walkthroughs
  • Beginner-friendly explanations of complex topics
  • Setup and installation instructions
  • Real-world examples and use cases

🎥 Video Tutorial

Prefer learning through video? Watch the accompanying tutorial:

Build an MCP Server from Scratch - YouTube

🔧 Technologies Used

  • FastAPI: Modern, fast web framework for building APIs
  • WebSockets: Real-time bidirectional communication
  • Pydantic: Data validation and serialization
  • OpenAI API: LLM integration for intelligent responses
  • SQLite: Database for server-side data storage
  • asyncio: Asynchronous programming for high performance

🚀 What You'll Build

By following this project, you'll create:

  1. A Capable Server that offers:

    • Tools (like calculators, database queries, text-to-SQL conversion)
    • Prompts (templates for LLM interactions)
    • Resources (configuration and user data access)

  2. An Intelligent Client that:

    • Connects to the server via WebSocket
    • Understands natural language queries
    • Selects appropriate tools automatically
    • Provides conversational responses

🎓 Learning Path

  1. Start Here: Open notebook.ipynb for the complete guide
  2. Explore the Code: Examine the server and client implementations
  3. Run the Application: Follow the setup instructions in the notebook
  4. Experiment: Try adding your own tools, prompts, or resources

📖 Key Concepts Covered

  • Model Context Protocol (MCP): Custom communication protocol design
  • WebSocket Session Management: Handling persistent connections
  • API Authentication: Secure access with API keys and quotas
  • Schema Validation: Using Pydantic for robust data handling
  • LLM Integration: Building AI-powered applications
  • Async Programming: Modern Python concurrency patterns