Practical AI Agent Development: Integrating PlayMCP and Spring AI

As businesses rush to integrate artificial intelligence, backend developers need reliable ways to connect large language models to existing enterprise systems. Building AI agents that can safely execute tasks and query databases requires structured frameworks rather than fragile custom scripts. This text-only course guides you through the fundamentals of AI agent development using PlayMCP and Spring AI. You will transition from basic API calls to designing autonomous agents capable of tool interaction, context retrieval, and structured decision-making within the Spring ecosystem. What you'll learn: - Understand the core concepts of the Model Context Protocol (MCP) and its role in modern agentic workflows. - Configure Spring AI to connect with leading large language models and manage conversation state. - Build custom tools and APIs that AI agents can discover and execute dynamically using PlayMCP. - Apply structured output techniques to ensure LLM responses conform to strict Java data models. - Design secure agentic workflows that prevent unauthorized tool execution and protect sensitive backend data. You will start by exploring foundational agent concepts and setting up your local Spring Boot development environment. From there, you will progress through step-by-step written tutorials on tool registration, context management, and end-to-end agent integration. This course is designed for backend developers, Java engineers, and AI enthusiasts who want to build production-ready AI agents, with no prior AI experience required. Start reading today to bridge the gap between enterprise Java and modern AI orchestration.