AI Agents & Agentic Workflows with Spring AI, MCP and Java

Model Context Protocol, Spring Boot, MCP Servers, ChatClient, ChatMemory, OpenAI, Gemini, Ollama, Integration Testing

What you'll learn
⚡ Build AI Agents using Spring AI and Java
⚡ Design Agentic Workflows and multi-turn reasoning systems
⚡ Implement MCP Servers using Spring Boot
⚡ Build and expose MCP Tools, Resources and Prompts
⚡ Integrate OpenAI, Gemini and local LLMs using Ollama
⚡ Build Human-in-the-Loop workflows using Elicitation
⚡ Handle asynchronous workflows using Progress Notifications
⚡ Write Integration Tests for MCP-based AI systems
⚡ Implement Structured Output and Prompt Engineering techniques
⚡ Use ChatClient, ChatMemory and Advisors effectively

Requirements
❗ No prior AI knowledge is required. We will start from the fundamentals with a hands-on approach.
❗ Knowledge of Java and Spring Boot is required.
❗ OpenAI and Gemini APIs may incur small usage costs. Expected cost for this course is approximately 1 USD.

Description

Build AI Agents and Agentic Workflows using Spring AI, MCP and Java.
This course is a deep-dive, architecture-first masterclass on building production-grade AI Agents and Agentic Workflows using Java, Spring AI and the Model Context Protocol (MCP).

What you will master
✨ Building AI Agents using Spring AI and Java

✨ Designing Agentic Workflows and multi-turn reasoning systems

✨ Understanding MCP Architecture and communication flow

✨ Implementing MCP Tools, Resources and Prompts

✨ Building Human-in-the-Loop workflows using Elicitation

✨ Handling asynchronous workflows using Progress Notifications

✨ Integrating OpenAI, Gemini and local models using Ollama

✨ Using ChatClient, ChatMemory and Advisors effectively

✨ Implementing Structured Output and Prompt Engineering techniques

✨ Designing AI-Powered Microservices using Spring Boot

✨ Writing Integration Tests for MCP-based systems

✨ Applying real-world AI architecture patterns and implementation best practices

By the end of the course, you will be able to
✨ Build production-grade AI Agents and Agentic Workflows using Spring AI and Java

✨ Design and implement MCP Servers with Tools, Resources and Prompts

✨ Integrate OpenAI, Gemini and local LLMs into Spring Boot applications

✨ Build context-aware AI systems using ChatMemory, Advisors and Structured Output

✨ Apply production-oriented AI architecture patterns, testing strategies and best practices

Throughout the course, we will build practical, production-style AI systems using Spring Boot, Spring AI and MCP.

Who this course is for
⭐ Java and Spring Developers exploring AI Agents and MCP

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