Automating UI Testing with AI and the Model Context Protocol (mCP)
Learn how to automate UI testing using AI and the Model Context Protocol (mCP), bridging the gap between AI and local data for efficient testing.
Course Timeline
🎙️ Introduction: AI-Powered UI Test Automation
Overview of using AI and large language models (LLMs) to automate UI testing without writing code, focusing on Anthropic Claude and the Model Context Protocol (mCP).
🤖 AI Agents and the Context Challenge
Discussion of recent releases of AI agents from Microsoft and GitHub, highlighting the need for context-aware AI to effectively interact with applications.
💡 Introducing the Model Context Protocol (mCP)
Explanation of mCP as an open-source standard for connecting AI assistants to local data and systems, addressing limitations of isolated AI models.
💻 Setting up mCP and Puppeteer Integration
Guide to setting up the mCP server and integrating it with Puppeteer for browser automation. Shows how to configure the mCP server for specific tools.
🚀 Automating a Website Test Scenario
A detailed demonstration of using Anthropic Claude and mCP with Puppeteer to automate a complete user interaction scenario on a sample website, including screenshots, login, and data entry.
⚠️ Troubleshooting and Improvements
Addresses issues encountered during the automation process, focusing on prompt engineering techniques for providing sufficient context to the AI model to enhance performance.
🎉 Conclusion: The Future of AI in UI Testing
Summary and insights into the future potential of AI in UI testing, highlighting the flexibility and extensibility of mCP for various tools.