Advanced MCP & Tool Calling for AI Agents

Overview

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Transform the way AI operates! Building intelligent, autonomous AI agents begins with mastering MCP architecture and tool calling. The issue? Many AI courses offer theory without the practical skills needed for real-world applications. In this Agentic AI course, you’ll learn to create advanced AI agents with Gemini and OpenAI tools. From registering tools and managing function calls to generating dynamic responses, you will discover how to integrate powerful AI functionalities effortlessly. You’ll also master building an MCP server, managing transport layers, and optimizing API routes for top-tier system performance. What sets this course apart? You’ll not only learn the theory but also build and deploy real AI systems that solve real-world problems, giving you the confidence to work in production environments. Ideal for developers and AI enthusiasts eager to create scalable, agent-driven systems. This course will arm you with the tools to make AI smarter and more autonomous. Get ready to build AI that thinks, learns, and adapts. Enroll now and start mastering MCP and tool calling today!

Syllabus

MCP Architecture and Native Tool Calling

Learn the fundamentals of MCP and native tool calling, including transport layers, architecture, and practical setup with Gemini and OpenAI tools. Implement initial tool functions and handle AI tool calls for real-world responses.

Building the MCP Server and Transport Layer

Build a fully functional MCP server with session management, tool registration, and client-server communication. Explore MCP transport layer setup, route configuration, and testing for agentic AI systems.

MCP Client Integration and Agentic AI System Design

Integrate MCP with OpenAI and Gemini clients, design agent loops, structured outputs, and AI-readable tool contexts. Test and refine your system to create scalable, real-world agentic AI applications.