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

Overview

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

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Subjects

Computer Science