About MCP Browser
MCP Browser is a headless browser interface built with Playwright for browser interaction and automation. It combines a web UI, WebSocket updates, and browser event subscriptions for AI agents.
Key features
- 01Playwright-based headless browser automation
- 02Web UI for browser interaction
- 03Real-time WebSocket updates
- 04Subscriptions to page, DOM, console, and network events
Use cases
- 01Automate browser tasks through a headless browser
- 02Monitor navigation, DOM, console, and network activity
- 03Receive browser event updates over WebSockets
MCP support
MCP Browser integrates with MCP for AI agents and reports browser and MCP client status. It exposes browser interaction and event subscription capabilities through its service.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Browser
A headless browser interface for the Model Control Protocol (MCP).
Features
- Headless browser automation using Playwright
- Web UI for browser interaction
- WebSocket communication for real-time updates
- Real-time browser event subscription system
- Integration with MCP for AI agents
Prerequisites
- Python 3.13+
- uv for dependency management
- Docker (for containerized usage)
Installation
One-Line Installation
To install MCP Browser on your Mac with one command:
curl -sSL https://raw.githubusercontent.com/neoforge-dev/mcp-browser/main/install_one_line.sh | bash
This command will download and run the installer with proper line ending handling to avoid common issues.
Manual Installation
For manual installation:
- Clone this repository
- Run the installer script:
git clone https://github.com/neoforge-dev/mcp-browser.git
cd mcp-browser
./install.sh
XQuartz Requirements
MCP Browser requires XQuartz (X11) for proper visualization. The installer will:
- Check if XQuartz is already installed and install it if needed
- Attempt to start the X11 server in various ways
- Prompt you to start it manually if automatic methods fail
If you encounter issues, see the Troubleshooting XQuartz Issues section.
Local Development
Setup with uv
# Clone the repository
git clone https://github.com/yourusername/mcp-browser.git
cd mcp-browser
# Install dependencies
uv venv .venv
source .venv/bin/activate
uv pip install -e .
# Install Playwright browsers
python -m playwright install
Running Locally
For a simple test without Xvfb:
./simple_test.sh
For a full test with Xvfb (requires X11):
./test_local.sh
Docker Deployment
Build and run using Docker Compose:
# Set your MCP secret
export MCP_SECRET=your_secret_key
# Build and run
docker-compose up --build
Or use the provided script:
./run.sh
Configuration
The following environment variables can be set:
MCP_SECRET: Secret key for MCP authenticationSERVER_PORT: Port to run the server on (default: 7665)PLAYWRIGHT_SKIP_BROWSER_DOWNLOAD: Set to 1 to skip browser download and run in headless-only mode
API Endpoints
GET /: Web UIGET /api/status: Get browser and MCP client statusWebSocket /ws: WebSocket endpoint for real-time communicationWebSocket /ws/browser/events: WebSocket endpoint for browser event subscriptionsGET /api/browser/subscribe: Subscribe to browser eventsGET /api/browser/unsubscribe: Unsubscribe from browser eventsGET /api/browser/subscriptions: List active event subscriptions
Event Subscriptions
The MCP Browser supports real-time event subscriptions via WebSockets. This allows clients to receive browser events as they happen, including:
- Page events (navigation, load, error)
- DOM events (mutations, changes)
- Console events (logs, warnings, errors)
- Network events (requests, responses, errors)
For detailed documentation and examples of the event subscription system, see:
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.