MCP Connector

Automate browser tasks and scrape web data with Playwright

MCP server that enables AI assistants to automate browsers with Playwright, supporting web scraping, screenshots, test generation, and device emulation across

Works with playwright

88
Spark score
out of 100
Updated 9 months ago
Source checked Sep 15, 2026
Version 1.0.0
Models
universal

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Why it matters

Run automated browser interactions and extract data from websites using Playwright's headless browser capabilities for testing, scraping, and workflow automation.

Outcomes

What it gets done

01

Drive browser navigation and interactions programmatically

02

Scrape structured data from web pages

03

Automate repetitive web-based workflows

04

Execute browser automation scripts for testing

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-playwright | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Playwright MCP Server

Playwright MCP Server provides browser automation capabilities to AI assistants through the Model Context Protocol. It enables LLMs to navigate web pages, take screenshots, scrape content, execute JavaScript, and generate Playwright test code in real browser environments. The server supports device emulation across 143 real device profiles with automatic configuration of viewports, user-agents, and touch events. Use this server when you need AI-driven browser testing across multiple device profiles, scraping dynamic content that requires JavaScript execution, or generating automation code from natural language descriptions. It fits scenarios where conversational browser control is more efficient than writing manual scripts, particularly for responsive design testing and exploratory automation.

What it does

Playwright MCP Server exposes browser automation capabilities to AI assistants through the Model Context Protocol. It enables LLMs to interact with web pages, capture screenshots, generate test code, scrape content, and execute JavaScript in real Chromium, Firefox, or WebKit environments. The server includes device emulation for 143 real device profiles with automatic user-agent, touch support, and device pixel ratios.

When to use - and when NOT to

Use this server when you need AI-driven browser automation for testing web applications across devices, scraping dynamic content that requires JavaScript execution, generating Playwright test code from natural language, or capturing visual snapshots of pages. It fits scenarios where you want to delegate browser interaction to an AI assistant rather than writing automation scripts manually.

The server supports both stdio mode (recommended for Claude Desktop) and HTTP mode. HTTP mode is available when running headed browser on systems without display or from worker processes of IDEs.

Inputs and outputs

You provide natural language commands to your AI assistant ("Test on iPhone 13", "Switch to iPad view", "Rotate to landscape") or direct tool calls. The server accepts device names, orientations, URLs, selectors, and JavaScript code as inputs.

The server processes browser automation requests and returns results from web page interactions. Device emulation automatically configures viewport dimensions, user-agents, and touch capabilities.

Integrations

The server integrates with Claude Desktop (stdio mode), VS Code with GitHub Copilot (HTTP mode or CLI installation), and any MCP-compatible client. It supports three browser engines: Chromium, Firefox, and WebKit. Installation methods include npm, mcp-get, Smithery, and Claude Code CLI.

Browser binaries install automatically on first use, or manually via Playwright CLI:

npm install -g @executeautomation/playwright-mcp-server

For Claude Desktop, configure stdio transport:

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

For VS Code, install via CLI:

code --add-mcp '{"name":"playwright","command":"npx","args":["@executeautomation/playwright-mcp-server"]}'

Device emulation example:

// Test on iPhone 13 with automatic user-agent, touch support, and device pixel ratio
await playwright_resize({ device: "iPhone 13" });

// Switch to iPad with landscape orientation
await playwright_resize({ device: "iPad Pro 11", orientation: "landscape" });

Who it's for

QA engineers who want AI assistance generating and executing browser tests across device profiles. Web developers testing responsive designs without maintaining device labs. Data engineers scraping JavaScript-heavy sites through conversational commands. Automation engineers building browser workflows with natural language instead of code.

Source README
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Playwright MCP Server 🎭

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A Model Context Protocol server that provides browser automation capabilities using Playwright. This server enables LLMs to interact with web pages, take screenshots, generate test code, web scrapes the page and execute JavaScript in a real browser environment.

mcp-playwright MCP server

✨ What's New in v1.0.10

🎯 Device Emulation with 143 Real Device Presets!

Test your web applications on real device profiles with a simple command:

// Test on iPhone 13 with automatic user-agent, touch support, and device pixel ratio
await playwright_resize({ device: "iPhone 13" });

// Switch to iPad with landscape orientation
await playwright_resize({ device: "iPad Pro 11", orientation: "landscape" });

// Test desktop view
await playwright_resize({ device: "Desktop Chrome" });

Natural Language Support for AI Assistants:

  • "Test on iPhone 13"
  • "Switch to iPad view"
  • "Rotate to landscape"

Supports 143 devices: iPhone, iPad, Pixel, Galaxy, and Desktop browsers with proper emulation of viewport, user-agent, touch events, and device pixel ratios.

📚 View Device Quick Reference | Prompt Guide

Screenshot

Documentation | API reference

Installation

You can install the package using either npm, mcp-get, or Smithery:

Using npm:

npm install -g @executeautomation/playwright-mcp-server

Using mcp-get:

npx @michaellatman/mcp-get@latest install @executeautomation/playwright-mcp-server

Using Smithery

To install Playwright MCP for Claude Desktop automatically via Smithery:

npx @smithery/cli install @executeautomation/playwright-mcp-server --client claude

Using Claude Code:

claude mcp add --transport stdio playwright npx @executeautomation/playwright-mcp-server
Installation in VS Code

Install the Playwright MCP server in VS Code using one of these buttons:

Install in VS Code
Install in VS Code Insiders

Alternatively, you can install the Playwright MCP server using the VS Code CLI:

# For VS Code
code --add-mcp '{"name":"playwright","command":"npx","args":["@executeautomation/playwright-mcp-server"]}'
# For VS Code Insiders
code-insiders --add-mcp '{"name":"playwright","command":"npx","args":["@executeautomation/playwright-mcp-server"]}'

After installation, the ExecuteAutomation Playwright MCP server will be available for use with your GitHub Copilot agent in VS Code.

Browser Installation

Automatic Installation (Recommended)

The Playwright MCP Server automatically installs browser binaries when you first use it. When the server detects that a browser is missing, it will:

  1. Automatically download and install the required browser (Chromium, Firefox, or WebKit)
  2. Display installation progress in the console
  3. Retry your request once installation completes

No manual setup required! Just start using the server, and it handles browser installation for you.

Manual Installation (Optional)

If you prefer to install browsers manually or encounter any issues with automatic installation:

# Install all browsers
npx playwright install

# Or install specific browsers
npx playwright install chromium
npx playwright install firefox
npx playwright install webkit

Browser Storage Location

Browsers are installed to:

  • Windows: %USERPROFILE%\AppData\Local\ms-playwright
  • macOS: ~/Library/Caches/ms-playwright
  • Linux: ~/.cache/ms-playwright

Configuration to use Playwright Server

Standard Mode (stdio)

This is the recommended mode for Claude Desktop.

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

Note: In stdio mode, logging is automatically directed to files only (not console) to maintain clean JSON-RPC communication. Logs are written to ~/playwright-mcp-server.log.

HTTP Mode (Standalone Server)

When running headed browser on systems without display or from worker processes of IDEs, you can run the MCP server as a standalone HTTP server:

Note for Claude Desktop Users: Claude Desktop currently requires stdio mode (command/args configuration). HTTP mode is recommended for VS Code, custom clients, and remote deployments. See CLAUDE_DESKTOP_CONFIG.md for details.

Starting the HTTP Server
# Using npx
npx @executeautomation/playwright-mcp-server --port 8931

# Or after global installation
playwright-mcp-server --port 8931

The server will start and display available endpoints:

==============================================
Playwright MCP Server (HTTP Mode)
==============================================
Port: 8931

ENDPOINTS:
- SSE Stream:     GET  http://localhost:8931/sse
- Messages:       POST http://localhost:8931/messages?sessionId=<id>
- MCP (unified):  GET  http://localhost:8931/mcp
- MCP (unified):  POST http://localhost:8931/mcp?sessionId=<id>
- Health Check:   GET  http://localhost:8931/health
==============================================
Client Configuration for HTTP Mode

⚠️ CRITICAL: The "type": "http" field is REQUIRED for HTTP/SSE transport!

For VS Code GitHub Copilot:

{
  "github.copilot.chat.mcp.servers": {
    "playwright": {
      "url": "http://localhost:8931/mcp",
      "type": "http"
    }
  }
}

For Custom MCP Clients:

{
  "mcpServers": {
    "playwright": {
      "url": "http://localhost:8931/mcp",
      "type": "http"
    }
  }
}

Important: Without "type": "http", the connection will fail.

For Claude Desktop: Use stdio mode instead (see Standard Mode above)

Use Cases for HTTP Mode
  • Running headed browsers on systems without display (e.g., remote servers)
  • Integrating with VS Code GitHub Copilot
  • Running the server as a background service
  • Accessing the server from multiple clients
  • Debugging with the /health endpoint
  • Custom MCP client integrations

Monitoring: The server includes a monitoring system that starts on a dynamically allocated port (avoiding conflicts). Check the console output for the actual port.

Note: For Claude Desktop, continue using stdio mode (Standard Mode above) for now.

Troubleshooting

"No transport found for sessionId" Error

Symptom: 400 error with message "Bad Request: No transport found for sessionId"

Solution:

  1. Check configuration includes "type": "http"

    {
      "url": "http://localhost:8931/mcp",
      "type": "http"  // ← This is REQUIRED!
    }
    
  2. Verify server logs show connection:

    # Should see these in order:
    # 1. "Incoming request" - GET /mcp
    # 2. "Transport registered" - with sessionId
    # 3. "POST message received" - with same sessionId
    
  3. Restart both server and client

Connection Issues

  • Server not starting: Check if port 8931 is available
  • External access blocked: This is by design (security). Server binds to localhost only
  • For remote access: Use SSH tunneling:
    ssh -L 8931:localhost:8931 user@remote-server
    

Testing

This project uses Jest for testing. The tests are located in the src/__tests__ directory.

Running Tests

You can run the tests using one of the following commands:

# Run tests using the custom script (with coverage)
node run-tests.cjs

# Run tests using npm scripts
npm test           # Run tests without coverage
npm run test:coverage  # Run tests with coverage
npm run test:custom    # Run tests with custom script (same as node run-tests.cjs)

The test coverage report will be generated in the coverage directory.

Running evals

The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.

OPENAI_API_KEY=your-key  npx mcp-eval src/evals/evals.ts src/tools/codegen/index.ts

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