MCP for devs - Master Model Context Protocol - Python/TS

Master the Model Context Protocol: Build Powerful AI Integrations with TypeScript or Python. Build AI agents with MCP

What you’ll learn

• Understand the Model Context Protocol architecture and how it enables AI agents to communicate with external tools and data sources
• Build fully functional MCP servers in TypeScript with tools, resources, and prompts for AI agents
• Develop production-ready MCP servers in Python to extend AI agent capabilities with custom integrations
• Implement HTTP and stdio transport protocols to enable flexible communication between AI agents and MCP servers
• Design MCP tools for AI agents to execute actions and resources for querying dynamic data
• Integrate external MCP servers to rapidly extend AI agent functionality without building from scratch
• Debug and test MCP implementations using the MCP Inspector and validation techniques.
• Deploy real-world MCP projects handling HTTP APIs, images, and state management for AI agents.

Requirements

• Basic programming experience with TypeScript or Python

Description

Unlock the Future of AI Development

Ready to take your AI applications to the next level? The Model Context Protocol (MCP) is revolutionizing how AI systems interact with external tools, data sources, and services. This comprehensive course will transform you from an MCP beginner into a confident builder of production-ready AI integrations.

What You'll Master

Foundation & Setup Start strong with a solid understanding of MCP architecture, hosts, and the ecosystem. You'll set up your development environment and connect your first external MCP within minutes.

Hands-On Building in Two Languages Choose your weapon—or learn both! Build complete MCP servers in TypeScript and Python with parallel implementations that let you compare approaches and pick what works best for your projects.

Core Concepts That Matter

• Navigate MCP transport layers including HTTP implementations

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

• Understand when to use Resources vs Tools for optimal performance

• Debug 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. 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 integrations

• Production-Ready Skills: Learn patterns used in real applications

• Hands-On Practice: Build actual working projects, not just toy examples

Who This Is For

• Developers looking to integrate AI into existing applications

• AI enthusiasts ready to move beyond basic chatbot interactions

• Backend engineers exploring modern AI architectures

• Anyone curious about building the infrastructure that powers next-generation AI applications

By the End of This Course

You'll confidently build custom MCP servers 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.

Who this course is for:

• Any developer who wants to learn MCP - Model Context Protocol

How can Learn Course this Course?

1.    Create Account / Login on Udemy.com

2.    Learn Course by Enroll in this Course

         

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