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

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Free Download AI Agents & Agentic Workflows with Spring AI, MCP and Java
Published 5/2026
Created by Vinoth Selvaraj
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 190 Lectures ( 11h 53m ) | Size: 5 GB

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
Homepage

https://www.udemy.com/course/ai-agents-java

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