Which integrations are available for this server?

Connects to Google's Gemini API using the Google API key for AI-driven browser automation tasks Provides integration with Ollama's local LLM hosting service, supporting customizable context settings and model parameters for browser automation Integrates with OpenAI's API for LLM functionality, enabling AI-powered browser control with customizable parameters

How do I use browser-use MCP server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@browser-use MCP server search for flights from New York to London next week" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

browser-use MCP server

Documentation License

Project Note: This MCP server implementation builds upon the browser-use/web-ui foundation. Core browser automation logic and configuration patterns are adapted from the original project.

AI-driven browser automation server implementing the Model Context Protocol (MCP) for natural language browser control.

Features

🧠 MCP Integration - Full protocol implementation for AI agent communication
🌐 Browser Automation - Page navigation, form filling, and element interaction
👁️ Visual Understanding - Screenshot analysis and vision-based interactions
🔄 State Persistence - Maintain browser sessions between tasks
🔌 Multi-LLM Support - OpenAI, Anthropic, Azure, DeepSeek integration

Related MCP server: Cloudflare Playwright MCP

Quick Start

Prerequisites

Python 3.11 or higher
uv (fast Python package installer)
Chrome/Chromium browser

Installation

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

"mcpServers": {
    "browser-use": {
      "command": "uvx",
      "args": [
        "mcp-server-browser-use",
      ],
      "env": {
        "OPENROUTER_API_KEY": "",
        "OPENROUTER_ENDPOINT": "https://openrouter.ai/api/v1",
        "OPENAI_ENDPOINT": "https://api.openai.com/v1",
        "OPENAI_API_KEY": "",
        "ANTHROPIC_ENDPOINT": "https://api.anthropic.com",
        "ANTHROPIC_API_KEY": "",
        "GOOGLE_API_KEY": "",
        "AZURE_OPENAI_ENDPOINT": "",
        "AZURE_OPENAI_API_KEY": "",
        "DEEPSEEK_ENDPOINT": "https://api.deepseek.com",
        "DEEPSEEK_API_KEY": "",
        "MISTRAL_API_KEY": "",
        "MISTRAL_ENDPOINT": "https://api.mistral.ai/v1",
        "OLLAMA_ENDPOINT": "http://localhost:11434",
        "ANONYMIZED_TELEMETRY": "true",
        "BROWSER_USE_LOGGING_LEVEL": "info",
        "CHROME_PATH": "",
        "CHROME_USER_DATA": "",
        "CHROME_DEBUGGING_PORT": "9222",
        "CHROME_DEBUGGING_HOST": "localhost",
        "CHROME_PERSISTENT_SESSION": "false",
        "BROWSER_HEADLESS": "false",
        "BROWSER_DISABLE_SECURITY": "false",
        "BROWSER_WINDOW_WIDTH": "1280",
        "BROWSER_WINDOW_HEIGHT": "720",
        "BROWSER_TRACE_PATH": "trace.json",
        "BROWSER_RECORDING_PATH": "recording.mp4",
        "RESOLUTION": "1920x1080x24",
        "RESOLUTION_WIDTH": "1920",
        "RESOLUTION_HEIGHT": "1080",
        "VNC_PASSWORD": "youvncpassword",
        "MCP_MODEL_PROVIDER": "anthropic",
        "MCP_MODEL_NAME": "claude-3-5-sonnet-20241022",
        "MCP_TEMPERATURE": "0.3",
        "MCP_MAX_STEPS": "30",
        "MCP_USE_VISION": "true",
        "MCP_MAX_ACTIONS_PER_STEP": "5",
        "MCP_TOOL_CALL_IN_CONTENT": "true"
    }
}

Local Development

"browser-use": {
  "command": "uv",
  "args": [
    "--directory",
    "/path/to/mcp-browser-use",
    "run",
    "mcp-server-browser-use"
  ],
  "env": {
    ...
  }
}

Development

# Install dev dependencies
uv sync

# Run with debugger
npx @modelcontextprotocol/inspector uv --directory . run mcp-server-browser-use

Troubleshooting

Browser Conflicts: Close all Chrome instances before starting.
API Errors: Verify API keys in environment variables match your LLM provider.
Vision Support: Ensure MCP_USE_VISION=true for screenshot analysis.

Provider Configuration

The server supports multiple LLM providers through environment variables. Here are the available options for MCP_MODEL_PROVIDER:

Provider	Value	Required Env Variables
Anthropic	`anthropic`	`ANTHROPIC_API_KEY` `ANTHROPIC_ENDPOINT` (optional)
OpenAI	`openai`	`OPENAI_API_KEY` `OPENAI_ENDPOINT` (optional)
Azure OpenAI	`azure_openai`	`AZURE_OPENAI_API_KEY` `AZURE_OPENAI_ENDPOINT`
DeepSeek	`deepseek`	`DEEPSEEK_API_KEY` `DEEPSEEK_ENDPOINT` (optional)
Gemini	`gemini`	`GOOGLE_API_KEY`
Mistral	`mistral`	`MISTRAL_API_KEY` `MISTRAL_ENDPOINT` (optional)
Ollama	`ollama`	`OLLAMA_ENDPOINT` (optional, defaults to localhost:11434)
OpenRouter	`openrouter`	`OPENROUTER_API_KEY` `OPENROUTER_ENDPOINT` (optional)

Notes:

For endpoints marked as optional, default values will be used if not specified
Temperature can be configured using MCP_TEMPERATURE (default: 0.3)
Model can be specified using MCP_MODEL_NAME
For Ollama models, additional context settings like num_ctx and num_predict are configurable