Using Playwright MCP in Cursor for Seamless Web Automation

Web automation is a game-changer for developers, enabling tasks like testing, data scraping, and form filling to be streamlined with minimal effort. With the rise of AI-powered IDEs like Cursor, integrating tools such as Playwright MCP (Model Context Protocol) allows developers to harness AI to control browsers directly from their coding environment. In this blog, we’ll explore how to set up and use Playwright MCP in Cursor, its benefits, and a practical example to get you started.

What is Playwright MCP?

Playwright MCP is an open-source server from Microsoft (GitHub — microsoft/playwright-mcp) that integrates Playwright, a powerful browser automation framework, with the Model Context Protocol (MCP). MCP enables AI agents, like those in Cursor, to interact with external tools using structured commands. Unlike traditional automation tools that rely on screenshots, Playwright MCP uses the browser’s accessibility tree to provide a lightweight, text-based representation of web pages, making it fast, reliable, and ideal for AI-driven workflows.

With Cursor’s AI capabilities (powered by models like Claude or GitHub Copilot), developers can issue natural language commands to automate browser tasks, such as navigating websites, clicking buttons, or extracting data, all within the IDE.

Why Use Playwright MCP in Cursor?

Combining Playwright MCP with Cursor offers several advantages:

• AI-Driven Automation: Use natural language to instruct Cursor’s AI to perform complex browser tasks, reducing manual coding.

• Efficiency: Playwright MCP’s Snapshot Mode uses accessibility data, avoiding the computational overhead of screenshot-based automation.

• Versatility: Automate tasks across Chromium, Firefox, and WebKit browsers, supporting testing, scraping, and more.

• Seamless Integration: Cursor’s support for MCP servers allows Playwright to work natively within the IDE, enhancing productivity.

• Open-Source: Both Playwright MCP and Cursor are backed by active communities, ensuring updates and flexibility.

Setting Up Playwright MCP in Cursor

To get started, you’ll need to configure Playwright MCP and connect it to Cursor. Follow these steps:

Prerequisites

• Node.js: Install Node.js (v14 or higher) from nodejs.org to run Playwright MCP.

• Cursor: Download and install Cursor from cursor.sh. Ensure you have a subscription or access to AI features (e.g., Claude or Copilot).

• Playwright MCP: No manual installation is required; it can be run via npx.

Step-by-Step Setup

1. Start the Playwright MCP Server:

• Open a terminal and run:

npx @playwright/mcp@latest

• This downloads and starts the Playwright MCP server, launching a headed Chromium browser (visible window) by default. To run headless (no visible window), use:

npx @playwright/mcp@latest --headless

• The server listens for MCP client connections, typically on http://localhost:8931/sse.

2. Configure Cursor for MCP:

• Open Cursor and go to Settings (gear icon or Ctrl+,/Cmd+,).

• Search for MCP in the settings panel.

• Add a new MCP server configuration:

{
  "mcpServers": {
    "playwright": {
      "name": "playwright",
      "command": "npx",
      "args": ["@playwright/mcp@latest"]
    }
  }
}

• Alternatively, use the command line to add the server:

cursor --add-mcp '{"name":"playwright","command":"npx","args":["@playwright/mcp@latest"]}'

• Verify the server is listed:

• Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P).

• Type MCP: List Servers and ensure Playwright appears.

3. Test the Connection:

• In Cursor, open the Chat panel (or use the Composer feature).

• Select the AI agent (e.g., Claude or Copilot) and enable the Playwright tool:

• Click the tools icon in the Chat panel and ensure playwright is selected.

• Test with a simple prompt:

Navigate to https://bluudit.com and tell me the page title.

• Click on the Run tool

• The AI should use Playwright MCP to open the website and return the title (e.g., “Bluudit Domain”).

4. Optional: Configure Advanced Settings:

• For remote server access, add — host 0.0.0.0 and — port <port> to the args in the MCP configuration.

• To use Vision Mode (screenshot-based), add — vision to the args.

• Example advanced configuration:

{
  "mcpServers": {
    "playwright": {
      "name": "playwright",
      "command": "npx",
      "args": ["@playwright/mcp@latest", "--headless", "--caps", "tabs,wait,files"],
      "url": "http://localhost:8931/sse"
    }
  }
}

Use Cases for Playwright MCP in Cursor

Here are some practical scenarios where Playwright MCP shines in Cursor:

1. Automated Testing:

• Test web applications by navigating pages, filling forms, and verifying UI elements.

• Example: “Log into my app at http://myapp.com/login and check if the dashboard loads.”

2. Web Scraping:

• Extract data like product prices, article headlines, or user reviews.

• Example: “Visit https://bluudit.com and list the top 5 post titles.”

3. Form Automation:

• Automate repetitive tasks like filling out contact forms or submitting data.

• Example: “Fill out the form at https://bluusit.com/contact with name ‘John Doe’ and email ‘john@example.com’.”

4. Debugging UI Issues:

• Use AI to validate UI changes by checking element states or styles.

• Example: “Go to my website and verify that the ‘Submit’ button is enabled.”

5. Workflow Automation:

• Chain multiple browser actions to automate complex tasks, like updating records in a web-based CRM.

• Example: “Log into my CRM, update the customer record for ‘Jane Smith,’ and save.”

Sample Example: Scraping News Headlines

Let’s walk through a practical example of using Playwright MCP in Cursor to scrape news headlines from a website and summarize them.

Scenario

We want Cursor’s AI to:

1. Navigate to https://bluudit.com.

2. Extract the top three post titles.

3. Summarise them in a concise bullet list.

Steps

1. Ensure the Server is Running:

• Start the Playwright MCP server:

npx @playwright/mcp@latest

2. Open Cursor:

• Launch Cursor and open the Chat panel.

• Select your AI agent (e.g., Claude) and enable the playwright tool.

3. Enter the Prompt:

• In the Chat panel, type:

Using Playwright, visit https://bluudit.com, extract the top three post titles, and summarize them in a bullet list.

4. Expected AI Behavior:

• The AI uses Playwright MCP tools:

• playwright_navigate: Opens https://bluudit.com.

• playwright_get_visible_text or playwright_evaluate: Extracts titles (e.g., by targeting elements with class=”titleline”).

• The AI processes the extracted text and generates a summary.

• Sample response:

Here are the top three post titles from https://bluudit.com, along with a brief summary for each:
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Accessibility Tree: Playwright MCP uses the browser’s accessibility tree to identify elements with roles like link or heading, making it easy to extract titles.

Tools Used:

• playwright_navigate: Navigates to the URL.

• playwright_evaluate: Runs JavaScript to select elements (e.g., document.querySelectorAll(‘.titleline a’)).

• playwright_get_visible_text: Retrieves text content from selected elements.

AI Processing: Cursor’s AI parses the structured output from Playwright MCP and generates a human-readable summary.

Tips for Success

1. Use Specific Prompts:

• Be clear in your instructions, e.g., “Click the button with text ‘Submit’” instead of “Click a button.”

• Specify selectors or accessibility roles if needed, e.g., “Extract elements with class ‘titleline’.”

2. Handle Errors:

• If the AI fails to find an element, try rephrasing the prompt or use Vision Mode ( — vision) for visual-based interactions.

• Check server logs in the terminal for debugging.

3. Optimize for Headless Mode:

• Use — headless for faster execution in CI/CD pipelines or when a visible browser isn’t needed.

4. Secure Sensitive Data:

• Avoid hardcoding credentials in prompts. Use Playwright’s — user-data-dir to manage browser profiles securely.

5. Leverage Cursor’s Composer:

• Use Cursor’s Composer feature to write code alongside Playwright automation, e.g., generating test scripts based on AI-driven browser interactions.

Security Considerations

• Permissions: Configure autoApprove in Cursor’s MCP settings to restrict Playwright actions (e.g., limit to navigate and get_visible_text tools).

• Browser Profiles: Clear the default profile (~/.cache/ms-playwright/mcp-chrome-profile on Linux) between sessions to prevent data retention.

• Network Security: If running on a remote server, secure the — host and — port with a firewall or VPN.

Community and Resources

Playwright MCP is part of the vibrant MCP ecosystem (mcp.so), with an active community (8.7k stars, 462 forks on GitHub as of April 2025). Explore these resources:

• Official Repository: GitHub — microsoft/playwright-mcp

• Community Forks: Check out executeautomation/mcp-playwright or xkiranj/playwright-universal-mcp for specialized use cases.

• Cursor Documentation: Visit cursor.sh/docs for AI and MCP integration guides.

Conclusion

Using Playwright MCP in Cursor empowers developers to automate web tasks with the power of AI, all within a single IDE. From testing web applications to scraping data and automating workflows, this integration streamlines development and boosts productivity. The setup is straightforward, and the example above demonstrates how easy it is to get started. Whether you’re a solo developer or part of a team, Playwright MCP in Cursor opens up exciting possibilities for AI-driven web automation.

Ready to try it? Fire up Cursor, start the Playwright MCP server, and let your AI assistant take the wheel!