Summary of "AI-Driven Test Automation with Playwright + Cursor + MCP Server"
Summary of Video: AI-Driven Test Automation with Playwright + Cursor + MCP Server
Main Technological Concepts and Tools:
- Playwright MCP Server: A server used to manage Playwright browser automation, with both official and unofficial/custom versions available.
- Cursor: An AI-powered tool integrated with the MCP server to automate code generation and test execution.
- AI-Driven Code Generation: Using the MCP server and Cursor to automatically generate Playwright test scripts based on natural language prompts.
- Page Object Model (POM): Organizing test automation code by separating page elements and actions into page-specific classes for maintainability.
- Playwright with Python & Pytest: The framework uses Python bindings for Playwright and Pytest as the test runner.
- Code Transpilation: The MCP server generates TypeScript code which Cursor automatically converts to Python or other frameworks like Selenium or Cypress.
Product Features and Workflow Demonstrated:
- Installing and Configuring the Custom MCP Server:
- Installation via npm globally.
- Configuration in Cursor settings through a JSON file (
mcp.json). - Ability to add multiple MCP servers, but only one (Playwright MCP Server) used here.
- Integration of Cursor with MCP Server:
- Setting up Cursor to communicate with the MCP server.
- Verifying MCP server is running by executing a simple test that opens a browser.
- Prompt-Based Framework Generation:
- Using a custom prompt to instruct Cursor to:
- Navigate to a demo website (susedemo.com).
- Automate login scenarios (valid login and locked-out user).
- Use the MCP server explicitly for browser automation.
- Generate code using the MCP server’s codegen feature.
- Organize the project structure following Page Object Model:
- Use Pytest as the test runner.
- Save all files inside a specific folder (avoid root directory clutter).
- Using a custom prompt to instruct Cursor to:
- Live Demonstration of Test Automation:
- Running the prompt in Cursor’s agent mode.
- Executing two scenarios:
- Valid login (standard user).
- Locked-out user scenario with error message validation.
- Cursor interacts with the MCP server to perform actions (navigate, fill, click, screenshot).
- MCP server captures actions and generates a TypeScript file, which Cursor converts to Python code.
- Framework Setup and Execution:
- Creation of the project directory structure and files.
- Adjusting the Playwright version in
requirements.txtto the latest stable version. - Setting up a Python virtual environment.
- Installing dependencies.
- Running tests with Pytest and confirming successful test execution.
- Analysis and Insights:
- The unofficial MCP server by "Execute Automation" offers more features (e.g., automatic code generation) compared to the official Playwright MCP Server.
- AI-driven automation can accelerate framework creation and test script generation but still requires human review and best practice enforcement.
- The approach is promising for quick demos and daily automation tasks but not yet a fully autonomous solution.
Guides/Tutorials Included:
- How to install and configure a custom Playwright MCP Server.
- How to integrate Cursor with the MCP server.
- How to create a prompt for automated test framework generation.
- How to run and validate Playwright tests using the generated framework.
- How to organize test automation projects using the Page Object Model in Python.
Main Speaker/Source:
- The video is presented by a content creator from Jung Media, who refers to himself as "Masters" throughout the video.
- The custom MCP server used is developed by Execute Automation, credited as an "amazing software test consultant" named Kartik.
This video serves as a practical tutorial and review of integrating AI tools (Cursor) with Playwright automation via a custom MCP server, showcasing automated test framework generation, execution, and best practices in structuring test code.
Category
Technology
