Build AI Agents with MCP - Model Context Protocol - TS/PY (Udemy.com)

Master the Model Context Protocol (MCP): Build MCP Servers in Python & TypeScript

Learn how to build MCP servers step by step and create production-ready AI agents powered by the Model Context Protocol (MCP). This hands-on course covers everything from MCP Python SDK and TypeScript SDK setup to deploying and publishing secure MCP servers for real-world LLM integration.

The Model Context Protocol is the emerging standard for connecting AI agents to external tools, data sources, and APIs. Whether you're building agentic AI solutions, integrating MCP clients with Large Language Models, or exploring how MCP vs other AI integration frameworks compares—this is your complete guide to Model Context Protocol development.

You'll master MCP server and MCP client architecture, understand STDIO vs Streamable HTTP transport layers, learn to build AI agents with MCP, and debug, test, and inspect your implementations like a pro. By the end, you'll confidently deploy and publish MCP solutions that are secure, scalable, and production-ready.

What You'll Master

Foundation & Setup
Start strong with a solid understanding of MCP architecture, hosts, and the ecosystem. Set up your development environment and connect your first external MCP within minutes—no prior experience required.

Hands-On Building in Two Languages
Choose your weapon—or learn both! Build complete MCP servers in TypeScript and Python with parallel implementations using the MCP Python SDK and TypeScript SDK. Compare approaches side by side and pick what works best for your projects.

Core Concepts That Matter

• Navigate MCP transport layers including STDIO vs Streamable HTTP implementations

• Master the three MCP primitives: Tools, Resources, and Prompts

• Understand when to use Resources vs Tools for optimal performance

• Learn to build secure MCP servers with proper authentication patterns

• Debug, test, and inspect your MCPs like a pro

Real-World Practice Project
Put theory into action with a complete, practical MCP project where you'll build a fully functional pizza ordering system using agentic AI patterns. Learn to handle HTTP calls, display images in responses, manage parameters, and track orders through a real-world implementation.

Why This Course?

• Parallel Language Support: Every major concept taught in both TypeScript and Python

• Progressive Learning: From "Hello World" to complex LLM integrations

• Production-Ready Skills: Learn patterns for real MCP deployment, not just toy examples

• Security-First Approach: Build and secure MCP servers for enterprise use

• Hands-On Practice: Build actual working AI agent projects

Who This Is For

• Developers looking to integrate AI agents into existing applications

• AI enthusiasts ready to move beyond basic chatbot interactions into agentic AI

• Backend engineers exploring modern AI architectures and LLM integration frameworks

• Anyone curious about building next-generation AI agent infrastructure

By the End of This Course

You'll confidently build custom MCP servers and MCP clients that extend AI capabilities with external tools, serve dynamic resources, and create seamless integrations. Whether you're building internal tools, commercial products, or experimental projects, you'll have the skills to make AI work with your systems, not just alongside them.

The future of AI is extensible. Learn to build it.