Patchright Lite MCP Server

Integrations

  • Provides a containerized version of the Patchright MCP server, accessible through Docker Hub for easy deployment and integration with AI tools

  • Allows GitHub Copilot to leverage Patchright's stealth browser automation capabilities through VS Code, enabling undetected web scraping and interaction

Patchright Lite MCP Server

A streamlined Model Context Protocol (MCP) server that wraps the Patchright Node.js SDK to provide stealth browser automation capabilities to AI models. This lightweight server focuses on essential functionality to make it easier for simpler AI models to use.

What is Patchright?

Patchright is an undetected version of the Playwright testing and automation framework. It's designed as a drop-in replacement for Playwright, but with advanced stealth capabilities to avoid detection by anti-bot systems. Patchright patches various detection techniques including:

  • Runtime.enable leak
  • Console.enable leak
  • Command flags leaks
  • General detection points
  • Closed Shadow Root interactions

This MCP server wraps the Node.js version of Patchright to make its capabilities available to AI models through a simple, standardized protocol.

Features

  • Simple Interface: Focused on core functionality with just 4 essential tools
  • Stealth Automation: Uses Patchright's stealth mode to avoid detection
  • MCP Standard: Implements the Model Context Protocol for easy AI integration
  • Stdio Transport: Uses standard input/output for seamless integration

Prerequisites

  • Node.js 18+
  • npm or yarn

Installation

  1. Clone this repository:
    git clone https://github.com/yourusername/patchright-lite-mcp-server.git cd patchright-lite-mcp-server
  2. Install dependencies:
    npm install
  3. Build the TypeScript code:
    npm run build

Usage

Run the server with:

npm start

This will start the server with stdio transport, making it ready to integrate with AI tools that support MCP.

Integrating with AI Models

Claude Desktop

Add this to your claude-desktop-config.json file:

{ "mcpServers": { "patchright": { "command": "node", "args": ["path/to/patchright-lite-mcp-server/dist/index.js"] } } }

VS Code with GitHub Copilot

Use the VS Code CLI to add the MCP server:

code --add-mcp '{"name":"patchright","command":"node","args":["path/to/patchright-lite-mcp-server/dist/index.js"]}'

Available Tools

The server provides just 4 essential tools:

1. browse

Launches a browser, navigates to a URL, and extracts content.

Tool: browse Parameters: { "url": "https://example.com", "headless": true, "waitFor": 1000 }

Returns:

  • Page title
  • Visible text preview
  • Browser ID (for subsequent operations)
  • Page ID (for subsequent operations)
  • Screenshot path

2. interact

Performs a simple interaction on a page.

Tool: interact Parameters: { "browserId": "browser-id-from-browse", "pageId": "page-id-from-browse", "action": "click", // can be "click", "fill", or "select" "selector": "#submit-button", "value": "Hello World" // only needed for fill and select }

Returns:

  • Action result
  • Current URL
  • Screenshot path

3. extract

Extracts specific content from the current page.

Tool: extract Parameters: { "browserId": "browser-id-from-browse", "pageId": "page-id-from-browse", "type": "text" // can be "text", "html", or "screenshot" }

Returns:

  • Extracted content based on the requested type

4. close

Closes a browser to free resources.

Tool: close Parameters: { "browserId": "browser-id-from-browse" }

Example Usage Flow

  1. Launch a browser and navigate to a site:
    Tool: browse Parameters: { "url": "https://example.com/login", "headless": false }
  2. Fill in a login form:
    Tool: interact Parameters: { "browserId": "browser-id-from-step-1", "pageId": "page-id-from-step-1", "action": "fill", "selector": "#username", "value": "user@example.com" }
  3. Fill in password:
    Tool: interact Parameters: { "browserId": "browser-id-from-step-1", "pageId": "page-id-from-step-1", "action": "fill", "selector": "#password", "value": "password123" }
  4. Click the login button:
    Tool: interact Parameters: { "browserId": "browser-id-from-step-1", "pageId": "page-id-from-step-1", "action": "click", "selector": "#login-button" }
  5. Extract text to verify login:
    Tool: extract Parameters: { "browserId": "browser-id-from-step-1", "pageId": "page-id-from-step-1", "type": "text" }
  6. Close the browser:
    Tool: close Parameters: { "browserId": "browser-id-from-step-1" }

Security Considerations

  • This server provides powerful automation capabilities. Use it responsibly and ethically.
  • Avoid automating actions that would violate websites' terms of service.
  • Be mindful of rate limits and don't overload websites with requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Patchright-nodejs by Kaliiiiiiiiii-Vinyzu
  • Model Context Protocol by modelcontextprotocol

Docker Usage

You can run this server using Docker:

docker run -it --rm dylangroos/patchright-mcp

Building the Docker Image Locally

Build the Docker image:

docker build -t patchright-mcp .

Run the container:

docker run -it --rm patchright-mcp

Docker Hub

The image is automatically published to Docker Hub when changes are merged to the main branch. You can find the latest image at: dylangroos/patchright-mcp

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A streamlined Model Context Protocol server that enables AI models to perform stealth browser automation using Patchright, avoiding detection by anti-bot systems while providing essential web interaction capabilities.

  1. What is Patchright?
    1. Features
      1. Prerequisites
        1. Installation
          1. Usage
            1. Integrating with AI Models
              1. Claude Desktop
              2. VS Code with GitHub Copilot
            2. Available Tools
              1. 1. browse
              2. 2. interact
              3. 3. extract
              4. 4. close
            3. Example Usage Flow
              1. Security Considerations
                1. License
                  1. Acknowledgments
                    1. Docker Usage
                      1. Building the Docker Image Locally
                      2. Docker Hub

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