Sandbox
@kontext-security/browser-use-mcp-server

MCP server for browser automation in Cursor and Claude

This is an MCP server that connects agent editors to a real browser through browser-use. It supports SSE and stdio transport, can stream the browser over VNC, and uses Playwright plus an OpenAI API key for tasks.

843 starsβ€’115 forksβ€’Pythonβ€’Updated 3mo ago
Who it's for

Builders who want their agent to open pages, click through flows, and report back from the browser.

What it delivers

You can let your agent browse the web instead of copying steps by hand.

What it does

Browser automation

Lets agents control a browser through browser-use.

Dual transport

Supports both SSE and stdio MCP connections.

VNC streaming

Lets you watch the browser session in real time.

Async tasks

Runs browser operations asynchronously.

Editor setup examples

Shows MCP client config paths for Cursor, Windsurf, and Claude.

How to get it

  1. 1Run
    # Install dependencies
    uv sync
    uv pip install playwright
    uv run playwright install --with-deps --no-shell chromium
  2. 2Run
    # Run directly from source
    uv run server --port 8000
  3. 3Run
    # 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

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.

πŸ”— 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 ChartStar History Chart

Files in the repo

Repository payloadβ€’20 top-level entries
  • .cursor
  • .github
  • server
  • src
  • .bandit.yml
  • .dockerignore
  • .env.example
  • .flake8
  • .gitignore
  • .mega-linter.yml
  • .pylintrc
  • .python-version
  • CODE_OF_CONDUCT.md
  • CONTRIBUTING.md
  • Dockerfile
  • LICENSE
  • pyproject.toml
  • pyrightconfig.json
  • README.md
  • uv.lock

Discussion (0)

Ask about usage, or say what you built with it

Sign in to join the discussion.

No comments yet. Be the first to say what this is good for.

More connectors

Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

86k

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph β€” average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

43k

Universal provider proxy for OpenAI Codex & Claude Code β€” use any LLM (Claude, Gemini, Grok, DeepSeek, Ollama…) with Codex CLI, App, SDK, and Claude Code

14k
okf-memory/
okf-agent-memory

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300Β΅s in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

547
tirth8205/
code-review-graph

Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.

31k
2akouwu/
reverify

Stop your AI from making things up β€” it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.

1.1k