Build Your Own MCP Servers with TypeScript -Beginner’s Guide
Published 11/2025
Duration: 5h 9m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 3.78 GB
Genre: eLearning | Language: English
Published 11/2025
Duration: 5h 9m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 3.78 GB
Genre: eLearning | Language: English
Learn how to turn your backend code into real AI-driven systems by building a Model Context Protocol (MCP) Server
What you'll learn
- Build a fully functional MCP Server in TypeScript from scratch
- Understand the four pillars of MCP — Tools, Resources, Prompts, and Sampling
- Transform an existing codebase into an AI-powered system by exposing CRUD operations as MCP tool functions
- Leverage AI Sampling and Prompt templates to generate intelligent responses, enrich missing data, and automate decision-making inside your own server logic.
- Package and deploy your MCP Server as an npm module and configure it with MCP clients
Requirements
- Basic knowledge on Javascript/Typescript
Description
TheModel Context Protocol (MCP)is redefining how Large Language Models interact with real-world systems — allowing AI to go beyond conversations and performactual tasks.This course,“Build Your Own MCP Server with TypeScript,”is a complete hands-on guide that takes you from the fundamentals of MCP to building and deploying a working server that bridges your backend code with AI models like Claude.
You’ll begin by understanding the core architecture of MCP — itsfour pillars: Tools, Resources, Prompts, and Sampling— and how each allows an AI to securely access databases, APIs, or system functions. Then, you’ll build a completee-commerce CRUD codebase in Node.js/TypeScript, where products can be added, updated, deleted, and fetched through natural language queries. By the end, you’ll see your LLM perform real database operations just by asking it in plain English.
Throughout the course, you’ll learn how todesign MCP-compliant endpoints,integrate AI-assisted actions, and evenpackage your server as an npm modulethat others can use with Claude Desktop. Whether you’re a developer, QA engineer, or AI enthusiast, this course transforms your understanding of how LLMs can act as intelligent system operators — executing real logic, not just generating text.
Wish you good luck. See you in the course
Who this course is for:
- QA Engineers, Test Automation Developers, and SDETs
- Backend Developers and Full-Stack Engineers
- AI Enthusiasts and Prompt Engineers
- Anyone curious about the next evolution of AI tooling
More Info