MCP Browser Use

What You Can Achieve With This MCP

This project aims to empower AI agents to perform web use, browser automation, scraping, and automation with Model Context Protocol (MCP) and Selenium.

The special feature of this MCP is that it can handle multiple agents accessing multiple browser windows. One does not need to start multiple Docker images, VMs, or computers to have multiple scraping agents. And one can still use one single browser profile across all agents. Each agent will have its own windows, and they will not interfere with each other.

This makes the handling of multiple agents seamless: Just start as many agents as you want, and it will just work! Use two Claude Code instances, one Codex CLI instance, one Gemini CLI instance and a fast-agent instance -- all on one computer, all using the same browser profile, and all working (somewhat) in parallel.

Our mission is to let AI agents complete any web task with minimal human supervision -- all based on natural language instructions.

Feature Highlights

HTML Truncation: The MCP allows you to configure truncation of the HTML pages. Other scraping MCPs may overwhelm the AI with accessibility snapshots or HTML dumps that are larger than the context window. This MCP will help you to manage the maximum page size by setting the MCP_MAX_SNAPSHOT_CHARS environment variable.
Multiple Browser Windows and Multiple Agents: You can connect multiple agents to this MCP independently, without requiring coordination on behalf of the agents. Each agent can work with the same browser profile, which is helpful when logins should persist across agents. Each agent gets their own browser window, so they do not interfere with each other. Uses Chrome DevTools Protocol TargetId to identify browser windows.

How to Use This MCP

Please refer to the MCP documentation on modelcontextprotocol.io.

Please note that you will need to install all dependencies in the Python environment that your MCP config file points to. For example, if you point to the python or python3 executable, you will point to the global Python environment. Usually it is preferred to point to a virtual environment such as:

/Users/yourname/code/mcp_browser_use/.venv/bin/python

If you have cloned this repository to your local code folder, your MCP config file should look like this:

{
    "mcpServers": {
        "mcp_browser_use": {
            "command": "/Users/janspoerer/code/mcp_browser_use/.venv/bin/python",
            "args": [
                "/Users/janspoerer/code/mcp_browser_use/mcp_browser_use"
            ]
        }
    }
}

and it will be here (in macOS): /Users/janspoerer/Library/Application Support/Claude/claude_desktop_config.json.

Please refer to the requirements.txt to see which dependencies you need to install.

Restart Claude to see if the JSON config is valid. Claude will lead to you the error logs for the MCP if something is off.

If the setup was successful, you will see a small hammer icon in the bottom-right of the "New Chat" window in Claude. Next to the hammer will be the number of functions that the MCP provides.

Click the hammer to see the available tools.

`.env` Variables

CHROME_PROFILE_NAME=Selenium
CHROME_EXECUTABLE_PATH= # Path to the Chrome executable.
CHROME_PROFILE_USER_DATA_DIR= # Path to the Chrome user data directory.
MAX_SNAPSHOT_CHARS=10000

Available Tools

Demo Video (YouTube)

Run Tests

We DO NOT want to use pytest-asyncio.

pip install -e ".[test]"`