Playwright logo

Playwright

Organization
automata-labs-team

MCP server for browser automation using Playwright

Publisherautomata-labs-team
Repositorymcp-server-playwright
LanguageJavaScript
Forks
50
Stars
291
Available tools
10
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Playwright exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 10 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    291 stars and 50 forks from the linked repository.

Table of Contents

Features

  • 🌐 Full browser automation capabilities
  • πŸ“Έ Screenshot capture of entire pages or specific elements
  • πŸ–±οΈ Comprehensive web interaction (navigation, clicking, form filling)
  • πŸ“Š Console log monitoring
  • πŸ”§ JavaScript execution in browser context

Installation

Installing via Smithery

To install MCP Server Playwright for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install @automatalabs/mcp-server-playwright --client claude

You can install the package using either npx or mcp-get:

Using npx:

bash
npx @automatalabs/mcp-server-playwright install

This command will:

  1. Check your operating system compatibility (Windows/macOS)
  2. Create or update the Claude configuration file
  3. Configure the Playwright server integration

The configuration file will be automatically created/updated at:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Using mcp-get:

bash
npx @michaellatman/mcp-get@latest install @automatalabs/mcp-server-playwright

Configuration

The installation process will automatically add the following configuration to your Claude config file:

json
{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": ["-y", "@automatalabs/mcp-server-playwright"]
    }
  }
}

Using with Cursor

You can also use MCP Server Playwright with Cursor, an AI-powered code editor. To enable browser automation in Cursor via MCP:

  1. Install Playwright browsers (if not already):

    bash
    npx playwright install
  2. Install MCP Server Playwright for Cursor using Smithery:

    bash
    npx -y @smithery/cli install @automatalabs/mcp-server-playwright --client cursor
  3. Configuration file setup:
    If you do not use Claude, the configuration file (claude_desktop_config.json) may not be created automatically.

    • On Windows, create a folder named Claude in %APPDATA% (usually C:\Users\<YourName>\AppData\Roaming\Claude).
    • Inside that folder, create a file named claude_desktop_config.json with the following content:
    json
    {
      "serverPort": 3456
    }
  4. Follow the remaining steps in the Installation section above to complete the setup.

Now, you can use all the browser automation tools provided by MCP Server Playwright directly from Cursor’s AI features, such as web navigation, screenshot capture, and JavaScript execution.

Note: Make sure you have Node.js installed and npx available in your system PATH.

Components

Tools

browser_navigate

Navigate to any URL in the browser

javascript
{
  "url": "https://stealthbrowser.cloud"
}

browser_screenshot

Capture screenshots of the entire page or specific elements

javascript
{
  "name": "screenshot-name",     // required
  "selector": "#element-id",     // optional
  "fullPage": true              // optional, default: false
}

browser_click

Click elements on the page using CSS selector

javascript
{
  "selector": "#button-id"
}

browser_click_text

Click elements on the page by their text content

javascript
{
  "text": "Click me"
}

browser_hover

Hover over elements on the page using CSS selector

javascript
{
  "selector": "#menu-item"
}

browser_hover_text

Hover over elements on the page by their text content

javascript
{
  "text": "Hover me"
}

browser_fill

Fill out input fields

javascript
{
  "selector": "#input-field",
  "value": "Hello World"
}

browser_select

Select an option in a SELECT element using CSS selector

javascript
{
  "selector": "#dropdown",
  "value": "option-value"
}

browser_select_text

Select an option in a SELECT element by its text content

javascript
{
  "text": "Choose me",
  "value": "option-value"
}

browser_evaluate

Execute JavaScript in the browser console

javascript
{
  "script": "document.title"
}

Resources

  1. Console Logs (console://logs)

    • Access browser console output in text format
    • Includes all console messages from the browser
  2. Screenshots (screenshot://<n>)

    • Access PNG images of captured screenshots
    • Referenced by the name specified during capture

License

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

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": [
        "-y",
        "@automatalabs/mcp-server-playwright"
      ]
    }
  }
}

Available Tools

  • browser_navigate

    Navigate to a URL

  • browser_screenshot

    Take a screenshot of the current page or a specific element

  • browser_click

    Click an element on the page using CSS selector

  • browser_click_text

    Click an element on the page by its text content

  • browser_fill

    Fill out an input field

  • browser_select

    Select an element on the page with Select tag using CSS selector

  • browser_select_text

    Select an element on the page with Select tag by its text content

  • browser_hover

    Hover an element on the page using CSS selector

  • browser_hover_text

    Hover an element on the page by its text content

  • browser_evaluate

    Execute JavaScript in the browser console

Use Playwright MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Playwright is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Playwright as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Playwright MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": [
        "-y",
        "@automatalabs/mcp-server-playwright"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Playwright MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Playwright MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Playwright to help me with this task?
Playwright
Sure. I read it.
Here is what I found using Playwright.

Frequently asked questions

What is the Playwright MCP server used for?

Playwright is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Playwright MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Playwright with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Playwright MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Playwright connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Playwright MCP to TypingMind?

Playwright runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Playwright MCP provide in TypingMind?

Playwright exposes 10 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Playwright MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Playwright requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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