"""
Basic usage example for mcp_use.

This example demonstrates how to use the mcp_use library with MCPClient
to connect any LLM to MCP tools through a unified interface.

Special thanks to https://github.com/microsoft/playwright-mcp for the server.
"""

import asyncio

from dotenv import load_dotenv
from langchain_openai import ChatOpenAI

from mcp_use import MCPAgent, MCPClient


async def main():
    """Run the example using a configuration file."""
    # Load environment variables
    load_dotenv()

    config = {
        "mcpServers": {"playwright": {"command": "npx", "args": ["@playwright/mcp@latest"], "env": {"DISPLAY": ":1"}}}
    }
    # Create MCPClient from config file
    client = MCPClient(config=config)

    # 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/mcp-use/mcp-use, give a star to the project and write
        a summary of the project.
        """,
        max_steps=30,
    )
    print(f"\nResult: {result}")


if __name__ == "__main__":
    # Run the appropriate example
    asyncio.run(main())
