Imagine a brilliant AI that knows everything about the world up to a certain date but cannot perform simple calculations or access your current calendar. In this lesson, you’ll explore the Model Context Protocol (MCP), a standardized way to connect Large Language Models (LLMs) to external data and tools. You’ll move beyond the theory and gain hands-on experience by building your very first MCP server.
By the end of this lesson, you’ll be able to:
Explain the core architecture of MCP, including hosts, clients, and servers
Set up a modern Python development environment using uv and Claude Desktop
Write and deploy an MCP server using the FastMCP framework
Connect a local server to an AI host using secure tunnelling with ngrok
These skills will not only help you understand how to extend the capabilities of AI models but also equip you with the practical knowledge to build scalable integrations that can bridge the gap between AI and real-world data.
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This content was released on Apr 10 2026. The official support period is 6-months
from this date.
An introduction to the Model Context Protocol (MCP), covering its architecture, purpose, and implementation. The lesson aims to teach students how to set up a development environment, write a basic MCP server using Python, and connect it to an LLM interface like Claude Desktop.
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