Building AI Integrations with Model Context Protocol (MCP)

The Model Context Protocol (MCP) is emerging as a core standard for how AI systems connect to tools, data, and external capabilities. This course provides a practical, end-to-end understanding of MCP—from first principles to real integrations—so you can design AI agents that scale cleanly across tools, models, and environments.

You’ll start by learning why MCP exists: the M × N integration problem that plagues modern AI systems, and how MCP reframes it into a composable, extensible architecture. From there, you’ll explore MCP’s core components, capabilities, and communication flow—building a clear mental model before touching any implementation.

Once the foundations are solid, the course moves into hands-on development. You’ll build MCP servers and clients from scratch, understand the JSON-RPC 2.0 message protocol that powers MCP, and work with streamable HTTP transport for real-world usage. Finally, you’ll integrate MCP servers with modern AI tooling like Claude Code and Cursor, showing how MCP fits naturally into today’s AI-powered development workflows.

Throughout the course, the focus stays on conceptual clarity, architectural correctness, and real-world applicability—not just getting something working, but understanding why it works and how it scales.

What You’ll Learn

• What MCP is, why it exists, and how it solves the AI integration problem

• How MCP defines and manages “context” through tools, resources, prompts, and sampling

• The roles and responsibilities of MCP hosts, clients, and servers

• How MCP communication flows from user request to server execution and back

• How to build and test MCP servers and clients using FastMCP

• How MCP uses JSON-RPC 2.0 and streamable HTTP transport

• How to integrate MCP with modern AI development tools like Claude Code and Cursor

Who This Course Is For

• AI engineers and developers building agentic systems

• Platform and infrastructure engineers evaluating MCP as a standard

• Developers integrating LLMs with tools, data sources, or internal systems

• Technical leaders who want a clear architectural understanding of MCP

Why This Course

Most MCP resources focus on snippets and setup. This course focuses on mental models, system design, and real integration patterns, so you can confidently explain MCP, implement it correctly, and use it as a long-term foundation for AI applications.

Enroll now and master the Model Context Protocol!

Hi, I’m Anton Voroniuk, and I’m here to help you unlock the power of AI and digital marketing. Over the past 17 years, I’ve trained over 1,000,000 students worldwide as a Google Academy Trainer and AI enthusiast.

With a master’s degree in search engine algorithms, machine learning, and AI, I’ve worked with Google and Facebook as a Premier Partner since 2017, staying ahead of the curve in AI-driven marketing. I’m also Google Cloud Certified as a Generative AI Leader, a recognition of my expertise in applying cutting-edge AI tools to real-world business challenges.

That passion led me to create AIMe Academy, a place where professionals like you can learn how to use AI to save time, grow your business, and achieve your goals faster.

If you’re ready to master AI and stay ahead of the competition, join me at AIMe Academy. Let’s take your skills to the next level!