English | Size:
Genre: eLearning
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
Build AI Agents and Agentic Workflows using Spring AI, MCP and Java. (Latest Spring Boot 4.0, Spring AI 2.0)
This entire course is about developing our own AI Agents From Scratch. It 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
rapidgator.net/file/c2d3f632843e92d486de5c4ff8d8239c/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part1.rar.html
rapidgator.net/file/914ffd77b95f1c27c6ac6fba1eafa5b7/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part2.rar.html
rapidgator.net/file/bd01699d0e3abb236d770c59e951f1fb/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part3.rar.html
rapidgator.net/file/e2bfe6065f5779df8123b5bbe3d6ea1e/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part4.rar.html
rapidgator.net/file/8694d6211f5aaca2e15b48a1b3d71c25/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part5.rar.html
trbt.cc/xj2i4id0pcq4/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part1.rar.html
trbt.cc/08vlkjjfjbap/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part2.rar.html
trbt.cc/fjh9cuhj306f/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part3.rar.html
trbt.cc/velx9sp5pgs4/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part4.rar.html
trbt.cc/lcb9sgdkhqrm/AIAgentsAgenticWorkflowswithSpringAIMCPandJava.part5.rar.html
If any links die or problem unrar, send request to
forms.gle/e557HbjJ5vatekDV9