Agent Orchestration and MCP: Build Multi-Agent AI Systems

About this course

This course contains the use of artificial intelligence.

AI agents are changing how we build software. But creating an agent that answers questions is one thing. Building a system where multiple agents collaborate, access enterprise data, execute tools, make decisions, and complete complex tasks is an entirely different challenge.

That's exactly what you'll learn in this course.

Agent Orchestration and MCP: Build Multi-Agent AI Systems is a hands-on, intermediate-level course designed to help developers, AI engineers, and solution architects move beyond basic chatbots and build practical, reliable, and secure agent-based applications.

You'll explore two important technologies shaping modern AI development: Model Context Protocol (MCP) and multi-agent orchestration.

MCP provides a standardized way for AI applications to connect with external tools, APIs, databases, and business systems. Agent orchestration takes things further by coordinating multiple specialized agents to complete tasks that would otherwise require complicated workflows or human intervention.

What You'll Learn

Throughout the course, you'll gain practical experience with:

• Model Context Protocol (MCP): Understand MCP architecture, servers, clients, tools, resources, prompts, and communication patterns.
• MCP Development: Build custom MCP servers and connect AI agents to external APIs, databases, and enterprise applications.
• Agent Orchestration: Design multi-agent workflows using LangGraph, Python, and supervisor-based architectures.
• Multi-Agent Collaboration: Implement agent routing, delegation, task handoffs, parallel execution, and shared workflow state.
• Security and Permissions: Implement authentication, authorization, tool-level permissions, and human approval checkpoints.

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