Browser Use MCP Server
About
Automate browser actions using natural language commands. Powered by Playwright and supports multiple LLM providers.
Details
- Author
- pietrozullo
- Categories
- Productivity, Automation, Other, AI
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Setup
Install Browser Use MCP Server in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/pietrozullo/browser-use-mcp
Follow the installation instructions in the repository README, then restart your MCP client.
Automate browser actions using natural language commands. Powered by Playwright and supports multiple LLM providers.
A FastMCP server that enables browser automation through natural language commands. This server allows Language Models to browse the web, fill out forms, click buttons, and perform other web-based tasks via a simple API.
Install with a specific provider (e.g., OpenAI)
pip install -e "git+https://github.com/yourusername/browser-use-mcp.git#egg=browser-use-mcp[openai]"
pip install -e "git+https://github.com/yourusername/browser-use-mcp.git#egg=browser-use-mcp[all-providers]"
Add the browser-use-mcp server to your MCP client configuration:
{ "mcpServers": { "browser-use-mcp": { "command": "browser-use-mcp", "args": ["--model", "gpt-4o"], "env": { "OPENAI_API_KEY": "your-openai-api-key", // Or any other provider's API key "DISPLAY": ":0" // For GUI environments } } } }
Replace"your-openai-api-key"with your actual API key or use an environment variable reference likeprocess.env.OPENAI_API_KEY.
import asyncio import os from dotenv import load_dotenv from langchain_openai import ChatOpenAI from mcp_use import MCPAgent, MCPClient async def main(): # Load environment variables load_dotenv() # Create MCPClient from config file client = MCPClient( config={ "mcpServers": { "browser-use-mcp": { "command": "browser-use-mcp", "args": ["--model", "gpt-4o"], "env": { "OPENAI_API_KEY": os.getenv("OPENAI_API_KEY"), "DISPLAY": ":0", }, } } } ) # Create LLM llm = ChatOpenAI(model="gpt-4o") # Create agent with the client agent = MCPAgent(llm=llm, client=client, max_steps=30) # Run the query result = await agent.run( """ Navigate to https://github.com, search for "browser-use-mcp", and summarize the project. """, max_steps=30, ) print(f"\nResult: {result}") if __name__ == "__main__": asyncio.run(main())
- Open Claude for Desktop
- Go to Settings → Experimental features
- Enable Claude API Beta and OpenAPI schema for API
- Add the following configuration to your Claude Desktop config file:
- Mac:~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:%AppData%\Claude\claude_desktop_config.json
{ "mcpServers": { "browser-use": { "command": "browser-use-mcp", "args": ["--model", "claude-3-opus-20240229"] } } }
- Start a new conversation with Claude and ask it to perform web tasks
The following LLM providers are supported for browser automation:
For more information check out:https://python.langchain.com/docs/integrations/chat/
You can create a.envfile in the project directory with your API keys:
OPENAI_API_KEY=your_openai_key_here # Or any other provider key
- API Key Issues: Ensure your API key is correctly set in your environment variables or.envfile.
- Provider Not Found: Make sure you've installed the required provider package.
- Browser Automation Errors: Check that Playwright is correctly installed withplaywright install chromium.
- Model Selection: If you get errors about an invalid model, try using the--modelflag to specify a valid model for your provider.
- Debug Mode: Use--debugto enable more detailed logging that can help identify issues.
- MCP Client Configuration: Make sure your MCP client is correctly configured with the right command and environment variables.
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