Mastering MCP: Building Advanced Agentic Applications

The advanced MCP course teaches you to build agentic apps, integrate LlamaIndex, ensure observability, deploy multi-server systems, and create an “Image Research Assistant.”

Intermediate

19 Lessons

7h

Updated yesterday

The advanced MCP course teaches you to build agentic apps, integrate LlamaIndex, ensure observability, deploy multi-server systems, and create an “Image Research Assistant.”

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This course includes

12 Playgrounds

This course includes

12 Playgrounds

Course Overview

This course teaches you how to use the Model Context Protocol (MCP) to build real-world AI applications. You’ll explore the evolution of agentic AI, why LLMs need supporting systems, and how MCP works, from its architecture and life cycle to its communication protocols. You’ll build both single- and multi-server setups through hands-on projects like a weather assistant, learning to structure prompts and connect resources for context-aware systems. You’ll also extend the MCP application to integrate externa...Show More

What You'll Learn

An understanding of the evolution from standalone LLMs to agentic AI and the need for Model Context Protocol

Comprehensive knowledge of MCP architecture, life cycle, and communication protocols

The ability to design and implement single-server MCP architectures, including prompt and resource integration, for context-aware AI

Proficiency in building and configuring modular multi-server MCP architectures for enhanced AI capabilities

Hands-on experience extending the MCP agent capabilities through RAG server implementation and integration with LlamaIndex

Practical knowledge of implementing authorization, authentication, logging, and debugging within MCP for robust AI systems

The skills to design, develop, and deploy a complete multimodal AI application, such as an “Image Research Assistant,” using MCP

What You'll Learn

An understanding of the evolution from standalone LLMs to agentic AI and the need for Model Context Protocol

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Course Content

1.

Getting Started

Develop advanced AI applications with Model Context Protocol for real-world solutions.
2.

Foundations of Model Context Protocol

Explore the evolution of Agentic AI and the Model Context Protocol for seamless AI integration.
3.

Implementing Single-Server MCP

Master single-server MCP architecture to create intelligent, context-aware weather assistants.
4.

Implementing Multi-Server MCP

Enhance AI capabilities through modular multi-server architecture and integrated prompts.

Building a Multi-Server MCP Using AWS Bedrock Agent

Cloud Lab

5.

Extending MCP with External Frameworks

Enhance agent capabilities through RAG server implementation and MCP-LlamaIndex integration.
6.

Observability in MCP

2 Lessons

Enhance security and reliability in MCP applications through robust authorization and effective debugging.
7.

Building an Image Research Assistant with MCP

4 Lessons

Develop an intelligent “Image Research Assistant” for efficient image analysis and research.
8.

What’s Next?

1 Lesson

Build your agentic AI skills and learn to develop advanced applications.

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