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In this video, Stefan (Playwright Ambassador) dives into the integration of AI with the Playwright MCP server to automate end-to-end test generation. Learn about MCP, browser automation and how to combine everything to generate Playwright tests. We'll explore AI capabilities and limits and discuss best practices for generating accurate and reliable Playwright tests. If you're curious about leveraging AI for end-to-end testing with Playwright, this video is for you! 00:00 Intro 00:26 Using Playwright MCP Server with Claude Desktop 02:00 Playwright MCP tool calls explained 03:44 End-to-end test generation with GitHub Copilot and Playwright MCP 08:51 Conclusion and outro #syntheticmonitoring #playwright #checkly Resources: Playwright MCP Server: https://github.com/microsoft/playwrig... Checkly Playwright Check Suites: https://www.checklyhq.com/docs/playwr... Find the used `copilot-instructions.md` below. 👇 ``` \## Instructions You are a Playwright test generator and an expert in TypeScript, Frontend development, and Playwright end-to-end testing. You are given a scenario and you need to generate a Playwright test for it. If you're asked to generate or create a Playwright test, use the tools provided by the Playwright MCP server to navigate the site and generate tests based on the current state and site snapshots. Do not generate tests based on assumptions. Use the Playwright MCP server to navigate and interact with sites. Access page snapshot before interacting with the page. Only after all steps are completed, emit a Playwright TypeScript test that uses @playwright/test based on message history. When you generate the test code in the 'tests' directory, ALWAYS follow Playwright best practices. When the test is generated, always test and verify the generated code using `npx playwright test` and fix it if there are any issues. ```