Build AI Agents with Model Context Protocol (MCP) (Video Course)

Description

Over 2 hours of video instruction

Overview:

Just as HTTP is the universal standard to connect web clients and servers, and FTP is the universal standard to connect file client and servers, Model Context Protocol (MCP) is the standard to connect AI agent clients to AI Agent servers.

In this course, you learn how to get started with creating AI agents that leverage the MCP to allow your agents to access MCP AI agent client tools. This course helps developers and managers understand the benefits of MCP and how it quickly enables the development of sophisticated AI agents.

This course provides you with hands-on demonstrations that enable developers using the official SDKs for the MCP for Python, Java, and Node.js. It also shows you how to configure and utilize the MCP server for the PostgreSQL database.

Skill Level:

• Beginner to Intermediate

Learn How To:

• Understand the benefits and practical applications of AI Agents that leverage the MCP 
• Configure MCP clients and build your own MCP servers 
• Get hands-on experience with creating AI agents using the STDIO and HTTP transports and create agents with the official MCP SDKs for Python, Java, and Node.js  
• Use MCP with your PostgreSQL database

Course requirement:

• Basic understanding of programming in any major programming language, such as Python, Java, Node.JS 
• Novice experience using ChatGPT or LLMs

Who Should Take This Course:

• Software developers 
• AI engineers 
• Software architects

About Pearson Video Training:  

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at  http://www.informit.com/video.  

Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson. 

Sample Content

Table of Contents

Introduction  

Get Started with Model Context Protocol (MCP) for AI Agents 

Learn the 3 domains of information  

Lab: Use AI to get real-time information: the weather  

Learn why MCP was created  

Understand why Walled Garden strategies fail  

Remember lessons learned from HTTP  

Learn how MCP is similar to HTTP 

Get familiar with MCP client applications  

Lab: Use AI with MCP to get real-time information: the weather  

Learn the Architecture of MCP Servers 

Learn the basic terms and terminology 

Get familiar with the message protocol  

Understand the types of transports used: STDIO and Streamable HTTP 

Recap: MCP client applications  

Understand when to apply tools versus resources 

Learn the purpose of prompts in your MCP servers 

Learn more about transports 

Deep Dive: Create an MCP Server in Python  

Focus on the implementation details 

Learn the dependencies 

Compare UV versus PIP 

Create the MCP server 

Set the transport 

Declare your tool 

Declare your prompts 

Lab: Run the Python MCP server in the MCP Inspector 

Deep Dive: Create an MCP Server in Java 

Focus on the implementation details 

Learn the dependencies 

Create the MCP server 

Set the transport 

Declare your tool 

Declare your prompts 

Lab: Run the Java MCP server in Postman 

Deep Dive: Create an MCP Server in Node.js 

Focus on the implementation details 

Learn the dependencies 

Create the MCP server 

Set the transport 

Declare your tool 

Declare your prompts 

Lab: Run the Node.js MCP server in the Claude Desktop 

Use MCP with the PostgreSQL Database 

Discuss the problem 

Learn the solution 

Configure your MCP server 

Lab: Run the PostgreSQL MCP server in the Claude Desktop 

Summary 

Updates

Submit Errata