browser-mcp

# browser-mcp A MCP (Model Control Protocol) server for [browser-use](https://github.com/browser-use/browser-use) library. This package allows AI agents to perform web browsing tasks through a standardized interface. ## Installation You can install the package using pip: ```bash pip install browser-mcp ``` Or with uv (recommended): ```bash uv pip install browser-mcp ``` After installation, you'll need to install Playwright's browser dependencies: ```bash playwright install ``` Alternatively, you can use the `browser-mcp-run` command which will automatically install these dependencies if they're missing. ## Setup For development, clone the repository and install in development mode: ```bash # Clone the repository git clone https://github.com/pranav7/browser-mcp.git cd browser-mcp # Install dependencies with uv uv pip install -e . # Or with pip pip install -e . ``` ## Environment Variables Create a `.env` file with your OpenAI API key: ``` OPENAI_API_KEY=your_api_key_here ``` ## Usage ### Running the MCP Server #### In Development Mode When working with the package in development mode, you can run it directly with Python: ```bash mcp dev browser_mcp/server.py ``` #### In Production After installing the package from PyPI, you can run it with uvx: ```bash uvx browser-mcp ``` The package is specifically designed to work with uvx, which allows for more efficient package loading and execution. #### With Automatic Dependency Check You can also use the `browser-mcp-run` command, which checks for and installs Playwright dependencies automatically before starting the server: ```bash browser-mcp-run ``` This ensures that all required Playwright browsers are installed on your system. ### Using as a Client ```python from mcp.client import Client async def main(): client = await Client.connect() # Perform a task with the browser result = await client.rpc("perform_task_with_browser", task="Search for the la…