MCP for QA Engineers: AI Automation with TypeScript (2026)

About this course

This course is designed for QA Engineers, SDETs, and Automation Engineers who want to build AI-integrated, production-ready QA systems using the Model Context Protocol (MCP) and TypeScript.

You will learn how to safely connect AI models to real QA systems—such as databases, services, and test utilities—so that AI can assist with validation, analysis, and automated decision-making in enterprise environments.

Build production-ready MCP servers using TypeScript to power AI-driven QA automation. Learn MCP fundamentals, create custom tools and resources, integrate real backend systems, and design agentic AI workflows that let LLMs interact with your applications safely and intelligently.

What you will be able to do after this course

Build MCP servers that expose QA-safe actions to AI models

Enable AI-assisted test data validation and verification

Allow LLMs to interact with read-only QA context securely

Design controlled AI-driven QA workflows, not autonomous chaos

Integrate AI with existing automation and backend systemsAI models like ChatGPT and Claude are powerful, but on their own they can only generate text. To unlock their real potential in software testing and automation, they need a safe and structured way to interact with real systems. That is exactly what Model Context Protocol (MCP) provides — and this course teaches you how to use it effectively for QA and automation.

In this course, you will learn how to build production-ready MCP servers using TypeScript, enabling AI models to read data, execute actions, and reason over real backend systems such as databases.

Through hands-on, step-by-step lessons, you’ll create custom MCP tools for CRUD operations, expose read-only resources for AI context, and design agentic AI workflows where the mo

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