AI Agents & MCP Explained for Smarter Software Testing

Build smarter testing workflows using MCP & AI Agents—Playwright, Atlassian, Chrome DevTools, and custom servers.

What you'll learn
- Understand the fundamentals of Model Context Protocol (MCP) and how it connects AI agents, tools, and environments for real-world software testing workflows.
- Set up and use MCP servers and clients, including Playwright MCP, GitHub MCP, Jira MCP, and others, directly inside VS Code.
- Build and customize AI-powered testing workflows using GitHub Copilot’s agentic capabilities, MCP tools, and real project integrations.
- Perform accessibility, console, and network audits through Playwright MCP and learn to extend MCP with your own tools.

Requirements
- Basic understanding of software testing or QA workflows (manual or automation).
- Familiarity with VS Code and running simple scripts or extensions.
- Some exposure to Playwright, GitHub Copilot, or test automation tools is helpful but not mandatory.
- A curious mindset to explore how AI and MCP can enhance modern testing.
- No prior experience with AI agents or MCP is required — everything is explained from the ground up.

Description
Note:This course contains the use of artificial intelligence to generate the voice-over.

Master AI Agents and the Model Context Protocol (MCP) to supercharge your software testing and automation workflows! This course is designed for software testers, QA engineers, and developers who want to leverage generative AI, agentic AI, and MCP to simplify complex tasks, automate repetitive processes, and gain actionable insights from your tools and data.

InModule 1: Introduction, you’ll understand why MCP is gaining massive attention in the AI and testing ecosystem. Learn what generative AI is, explore the concept of AI Agents, and discover the differences between AI Agents, agentic AI, and traditional automation.

Module 2: Agentic AI in Actiondives into real-world applications. Experience GitHub Copilot’s agentic capabilities, fetch and scrape data using Copilot Agent Mode, try custom chat modes, and explore popular AI Agent frameworks to boost productivity and testing efficiency.

InModule 3: Model Context Protocol, gain hands-on experience with MCP. Learn to set up Playwright MCP for accessibility audits, network traffic tracking, console message monitoring, and authenticated session access. Use Chrome DevTools MCP for automated browser debugging, Atlassian MCP to connect Jira & Confluence with GitHub Copilot, MCP Toolbox to query databases without SQL, and Gemini CLI to interact with GitHub MCP servers.

Finally,Module 4: Hands-On With MCPteaches you how to build and test your own MCP server, define custom tools, inspect server connections, and understand how MCP enables AI clients to seamlessly communicate with external systems.

By the end of this course, you’ll be able to create intelligent, automated workflows that save time, reduce errors, and unlock the full potential of AI in your testing and development processes.

Who this course is for:
- Software Testers and QA Engineers who want to move beyond traditional testing and automation and explore AI-driven testing.
- Test Automation Engineers looking to integrate GitHub Copilot, Playwright, and other MCP tools into their workflow.
- Developers and SDETs interested in understanding how AI agents and the Model Context Protocol (MCP) can enhance productivity.
- Tech enthusiasts and learners curious about the next generation of automation using AI and agentic systems.
- Anyone who wants to future-proof their testing skills by learning how MCP connects AI agents, tools, and test environments.
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