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"""
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"}}}
}
client = MCPClient(config=config)
# Create LLM
llm = ChatOpenAI(model="gpt-5")
# Create agent with the client
agent = MCPAgent(llm=llm, client=client, max_steps=30, pretty_print=True)
# 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())