MCP Servers & Agentic AI Architecture
About this course
Imagine building an AI that doesn’t wait for prompts but actively runs your backend, selects the right tools, and completes tasks end-to-end. Most AI applications are limited to generating answers. But real-world systems require structured execution, intelligent workflows, and scalable architecture and that’s where most developers fall behind. In this course, you will build MCP-based AI systems that go beyond responses. You will implement backend logic using services and controllers, build MCP servers, and define tools, resources, and prompts to enable AI to execute in a controlled manner. Get hands-on experience with tool deployments using Gemini and OpenAI, request-response cycles, and agent controllers that cover autonomous workflows. You will also work with vector databases such as ChromaDB and pgVector to enhance context retrieval, accelerate data ingestion, and produce intelligent AI outputs. This Agentic AI course is designed for developers looking to level up and build agent-powered, production-ready systems for real-world industry needs. Stop building AI that just responds start building AI that operates. Enroll now and lead the next wave of intelligent systems.
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What you'll learn
- implement backend logic using services and controllers
- build MCP servers
- define tools and resources for controlled AI execution
- deploy tools using Gemini and OpenAI
- utilize vector databases for context retrieval
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