import asyncio
import os
from browser_use import Agent, Controller
from browser_use.mcp.client import MCPClient
from browser_use.llm import ChatOpenAI
async def main():
"""
Example showing how to connect to a Browser-use MCP server deployed on Heroku.
This example demonstrates how to:
1. Connect to a Heroku-deployed Browser-use MCP server
2. Register the MCP server's tools to a controller
3. Create and run an agent that uses these tools
Environment Variables Required:
- HEROKU_MCP_URL: The URL of your Heroku MCP server (e.g., https://your-app-name.herokuapp.com/mcp)
- HEROKU_MCP_TOKEN: Your authentication token for the Heroku MCP server
- OPENAI_API_KEY: Your OpenAI API key
"""
# Initialize controller
controller = Controller()
# Connect to the Heroku-deployed Browser-use MCP server
browser_client = MCPClient(
server_name="browser-use",
url=os.environ.get("HEROKU_MCP_URL"),
token=os.environ.get("HEROKU_MCP_TOKEN"),
)
try:
# Connect to the MCP server
await browser_client.connect()
print("Successfully connected to Browser-use MCP server")
# Register the MCP server's tools to the controller
await browser_client.register_to_controller(controller)
print("Successfully registered MCP tools to controller")
# Create an agent with the MCP-enabled controller
agent = Agent(
task="Compare the price of gpt-4o and DeepSeek-V3",
llm=ChatOpenAI(model="gpt-4o", temperature=1.0),
controller=controller
)
# Run the agent
await agent.run()
finally:
# Ensure we disconnect from the MCP server
await browser_client.disconnect()
print("Disconnected from Browser-use MCP server")
if __name__ == "__main__":
asyncio.run(main())
