#Module 1 - MCP Intro

Module 1 – Introduction to Model Context Protocol (MCP)

Model Context Protocol (MCP) allows AI agents to interact safely with tools, code, and structured data. In this 12‑module course, we will build an Attendance Tracking System for a university department:

• 2 Courses
• 8-semester program & 4-semester program
• 14 Staff
• 6 Subjects per semester
• 60 Students per semester
• Odd: 1,3,5,7 | Even: 2,4,6,8
• Each semester has a 40-hour weekly timetable

🔹 What You Will Learn in Module 1

• What MCP is
• Why MCP is useful for structured academic workflow systems
• How our Attendance System will use MCP
• Set up the MCP-compatible project folder

📌 Step 1 — Create Project Structure

Run the following commands to create the project folder for the upcoming modules:

mkdir university-attendance-mcp
cd university-attendance-mcp
mkdir mcp_server
mkdir database
mkdir models
mkdir logs

📌 Step 2 — Create MCP Server Boilerplate

We will create a simple MCP server using Python.

# file: mcp_server/server.py
from mcp import MCPServer

app = MCPServer(name="UniversityAttendanceMCP")

@app.tool()
def ping():
    return {"message": "MCP Server is running"}

if __name__ == "__main__":
    app.run()

📌 Step 3 — Install Dependencies

Install MCP SDK and required libraries:

pip install model-context-protocol uvicorn fastapi

📌 Step 4 — Run the MCP Server

python mcp_server/server.py

If everything is correct, MCP should print:

{"message": "MCP Server is running"}