mcpField
B
browser-use-mcp-server

browser-use-mcp-server

Local
kontext.securityBrowser Automation849Updated 68w ago

About browser-use-mcp-server

browser-use-mcp-server is an MCP server that lets AI agents in clients such as Cursor, Windsurf and Claude control a web browser through browser-use. It supports both SSE and stdio transports and offers VNC streaming to watch browser sessions live.

Key features

  1. 01AI agent control of browser actions
  2. 02SSE and stdio transport support
  3. 03VNC streaming of browser sessions
  4. 04Asynchronous browser task execution
  5. 05Docker setup for an isolated environment

Use cases

  1. 01Asking Cursor to open a web page and extract information
  2. 02Watching an automated browsing session through VNC
  3. 03Running browser automation in an isolated container

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

browser-use-mcp-server

Twitter URL Discord PyPI version

An MCP server that enables AI agents to control web browsers using browser-use.

🌐 Want to Vibe Browse the Web? Open-source AI-powered web browser - Vibe Browser.

🔗 Managing multiple MCP servers? Simplify your development workflow with agent-browser

Prerequisites

# Install prerequisites
curl -LsSf https://astral.sh/uv/install.sh | sh
uv tool install mcp-proxy
uv tool update-shell

Environment

Create a .env file:

OPENAI_API_KEY=your-api-key
CHROME_PATH=optional/path/to/chrome
PATIENT=false  # Set to true if API calls should wait for task completion

Installation

# Install dependencies
uv sync
uv pip install playwright
uv run playwright install --with-deps --no-shell chromium

Usage

SSE Mode
# Run directly from source
uv run server --port 8000
stdio Mode
# 1. Build and install globally
uv build
uv tool uninstall browser-use-mcp-server 2>/dev/null || true
uv tool install dist/browser_use_mcp_server-*.whl

# 2. Run with stdio transport
browser-use-mcp-server run server --port 8000 --stdio --proxy-port 9000

Client Configuration

SSE Mode Client Configuration
{
  "mcpServers": {
    "browser-use-mcp-server": {
      "url": "http://localhost:8000/sse"
    }
  }
}
stdio Mode Client Configuration
{
  "mcpServers": {
    "browser-server": {
      "command": "browser-use-mcp-server",
      "args": [
        "run",
        "server",
        "--port",
        "8000",
        "--stdio",
        "--proxy-port",
        "9000"
      ],
      "env": {
        "OPENAI_API_KEY": "your-api-key"
      }
    }
  }
}
Config Locations
ClientConfiguration Path
Cursor./.cursor/mcp.json
Windsurf~/.codeium/windsurf/mcp_config.json
Claude (Mac)~/Library/Application Support/Claude/claude_desktop_config.json
Claude (Windows)%APPDATA%\Claude\claude_desktop_config.json

Features

  • Browser Automation: Control browsers through AI agents
  • Dual Transport: Support for both SSE and stdio protocols
  • VNC Streaming: Watch browser automation in real-time
  • Async Tasks: Execute browser operations asynchronously

Local Development

To develop and test the package locally:

  1. Build a distributable wheel:

    # From the project root directory
    uv build
    
  2. Install it as a global tool:

    uv tool uninstall browser-use-mcp-server 2>/dev/null || true
    uv tool install dist/browser_use_mcp_server-*.whl
    
  3. Run from any directory:

    # Set your OpenAI API key for the current session
    export OPENAI_API_KEY=your-api-key-here
    
    # Or provide it inline for a one-time run
    OPENAI_API_KEY=your-api-key-here browser-use-mcp-server run server --port 8000 --stdio --proxy-port 9000
    
  4. After making changes, rebuild and reinstall:

    uv build
    uv tool uninstall browser-use-mcp-server
    uv tool install dist/browser_use_mcp_server-*.whl
    

Docker

Using Docker provides a consistent and isolated environment for running the server.

# Build the Docker image
docker build -t browser-use-mcp-server .

# Run the container with the default VNC password ("browser-use")
# --rm ensures the container is automatically removed when it stops
# -p 8000:8000 maps the server port
# -p 5900:5900 maps the VNC port
docker run --rm -p8000:8000 -p5900:5900 browser-use-mcp-server

# Run with a custom VNC password read from a file
# Create a file (e.g., vnc_password.txt) containing only your desired password
echo "your-secure-password" > vnc_password.txt
# Mount the password file as a secret inside the container
docker run --rm -p8000:8000 -p5900:5900 \
  -v $(pwd)/vnc_password.txt:/run/secrets/vnc_password:ro \
  browser-use-mcp-server

Note: The :ro flag in the volume mount (-v) makes the password file read-only inside the container for added security.

VNC Viewer
# Browser-based viewer
git clone https://github.com/novnc/noVNC
cd noVNC
./utils/novnc_proxy --vnc localhost:5900

Default password: browser-use (unless overridden using the custom password method)

VNC Screenshot

VNC Screenshot

Example

Try asking your AI:

open https://news.ycombinator.com and return the top ranked article

Support

For issues or inquiries: cobrowser.xyz

Star History

Star History Chart

Comments

Markdown supported

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.