Building AI Agents with Model Context Protocol: From Specification to Implementation

Overview

Explore the Model Context Protocol for AI agent development, learning how to implement standardized interactions with external tools and resources using Spring AI MCP and Java SDK.

Syllabus

- Introduction to AI Agents -- Definition and Characteristics of AI Agents -- Overview of AI Agent Development Process - Overview of Model Context Protocol (MCP) -- Introduction to MCP -- Advantages of Using MCP in AI Development - Setting Up Your Development Environment -- Installing Java SDK -- Setting Up Spring AI for MCP - Fundamental Concepts of Spring AI MCP -- Architecture of Spring AI MCP -- Key Components and Their Roles - MCP Specification and Design -- Writing MCP Specifications -- Defining Interactions with External Tools - Implementing AI Agents with MCP -- Creating Simple AI Agents using Java SDK -- Integrating MCP Specifications in Agent Development - Advanced MCP Features -- Handling Complex Interactions -- Extending MCP for Custom Applications - Testing and Debugging AI Agents -- Best Practices for Testing MCP-based Agents -- Using Debugging Tools and Techniques - Case Studies -- Real-world Applications of MCP in AI -- Analyzing Successful MCP Implementations - Future Trends in MCP and AI Agent Development -- Emerging Technologies and Methodologies -- Potential Developments in MCP Standards - Course Wrap-Up -- Recap of Key Concepts -- Resources for Further Learning and Exploration

Taught by

Tags