Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Understand how Model Context Protocol (MCP) works and why it's the emerging standard for connecting AI agents to tools, data, and external systems
- Break down MCP's core architecture: Host, Server, and Client roles, and how they communicate
- Trace the evolution from standalone LLMs to autonomous, context-aware AI agents
- Build a working MCP server and client from scratch with prompt and resource features
- Design AI agents that dynamically discover and use tools through structured protocol communication
Why choose this course?
Want to Build the Next Generation of Agentic AI?
MCP is the backbone of modern agentic systems. Why? Because it standardizes how AI models connect with tools, data, and external environments, which is an essential step toward creating intelligent, autonomous agents.
It’s the Language of Agentic Automation
MCP is a protocol layer that will power the next wave of AI systems. Learning MCP means understanding how autonomous AI will communicate, collaborate, and scale in the real world.
Understand What Makes MCP Different
Forget brittle API bridges. MCP introduces a structured protocol with modular roles, Host, Server, and Client, that bring order, scalability, and reliability. You’ll learn how each piece communicates to make your agents adaptive.
Create an End-to-End MCP Application
Code your own MCP server and client from scratch, add prompt and resource features, and watch your AI agent dynamically discover and use them. Through guided coding, you’ll gain the confidence to engineer real-world.
Learning Roadmap
1.
Getting Started
Getting Started
Get an overview of Model Context Protocol for integrating AI and automating workflows.
2.
Introduction to MCP
Introduction to MCP
Explore the core understanding and architecture of Model Context Protocol.
3.
Building an Application with MCP
Building an Application with MCP
4 Lessons
4 Lessons
Explore the development of an MCP server and client for enhanced AI interactions.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
MCP is one of those technologies where theoretical knowledge is widespread, yet production-grade implementation experience remains limited. The protocol itself is well-designed, but the documentation assumes a lot, the ecosystem is young, and most engineers I talk to have the same question: where do I actually start?
That's why I built this course. As someone who has spent years researching and teaching AI systems (from neural networks and adaptive systems to the production-ready GenAI architectures we cover in other courses on Educative) I wanted to create the resource I wish existed when I first started working with MCP: a clear, structured, hands-on path from zero to a working MCP application.
You'll start with the fundamentals: why agentic systems need a protocol like MCP in the first place, and how MCP's architecture (Host, Server, Client) solves the integration problems that have plagued AI tooling. From there, you'll build. You'll code an MCP server, wire up a client, add prompt and resource capabilities, and see your agent dynamically discover and use tools through the protocol. Everything runs in-browser. No local setup required.
ABOUT THE AUTHOR
Khayyam Hashmi
Computer scientist and Generative AI and Machine Learning specialist. VP of Technical Content @ educative.io.
Trusted by 2.9 million developers working at companies
A
Anthony Walker
@_webarchitect_
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Evan Dunbar
ML Engineer
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Software Developer
Carlos Matias La Borde
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Souvik Kundu
Front-end Developer
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Vinay Krishnaiah
Software Developer
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