Fixing runtime errors in web applications, especially those that require browser interaction or appear in stages, can be a tedious back-and-forth. This lesson demonstrates how to create a powerful, automated debugging loop using Playwright MCP integrated into Cursor IDE via custom Rules, allowing the AI to interact with your live application, identify errors, and iteratively fix them.
Workflow demonstrated in this lesson:
- Install and configure the Playwright MCP server in Cursor settings.
- Create a custom Cursor Rule (e.g., "autofix") instructing the AI to:
- Use Playwright MCP to open a specified URL in a browser.
- Check for any errors displayed on the page.
- Automatically attempt to fix those errors in your codebase.
- Iterate this process until all errors are resolved.
- Invoke the custom rule within Cursor's AI Agent, providing the application's URL.
- Observe the AI agent launch Playwright, navigate the browser, identify errors, and apply code changes.
- For errors hidden behind UI elements (like an error button), provide a screenshot to the AI, instructing it to interact with the UI to reveal and then fix subsequent errors.
Key benefits:
- Automated Debugging Cycle: Let the AI handle the repetitive task of launching, testing, and fixing common web application errors.
- Iterative Problem Solving: The AI can tackle multiple errors sequentially, making changes and re-testing.
- Browser Interaction: Leverages Playwright to understand the application's state directly from the browser.
- Visual AI Assistance: Use screenshots to guide the AI in interacting with UI elements to uncover and fix deeper issues.
- Reduced Manual Effort: Spend less time manually debugging and more time on feature development.
By combining Playwright MCP with Cursor's AI Agent and custom Rules, you can significantly streamline your web development workflow, turning a frustrating debugging process into an automated one.