Quickstart

from typing import Annotated
from mcp.types import ToolAnnotations
from pydantic import Field
from mcp_use import MCPServer

server = MCPServer(name="Weather Server", version="1.0.0")

@server.tool(
    name="get_weather",
    description="Get current weather information for a location",
    annotations=ToolAnnotations(readOnlyHint=True, openWorldHint=True),
)
async def get_weather(
    city: Annotated[str, Field(description="City name")],
) -> str:
    return f"Temperature: 72°F, Condition: sunny, City: {city}"

# Start server with auto-inspector
server.run(transport="streamable-http", port=8000)
# Inspector at http://localhost:8000/inspector

import asyncio
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI
from mcp_use import MCPAgent, MCPClient

async def main():
    load_dotenv()
    
    # Configure MCP servers
    config = {
        "mcpServers": {
            "playwright": {
                "command": "npx",
                "args": ["@playwright/mcp@latest"],
            }
        }
    }
    
    # Create client and agent
    client = MCPClient.from_dict(config)
    llm = ChatOpenAI(model="gpt-4o")
    agent = MCPAgent(llm=llm, client=client, max_steps=30)
    
    # Run a query
    result = await agent.run(
        "Find the best restaurant in San Francisco using Google Search"
    )
    print(f"Result: {result}")

if __name__ == "__main__":
    asyncio.run(main())

async for chunk in agent.stream("Find restaurants in Tokyo"):
    print(chunk["messages"], end="", flush=True)

config = {
    "mcpServers": {
        "airbnb": {
            "command": "npx",
            "args": ["-y", "@openbnb/mcp-server-airbnb"]
        },
        "playwright": {
            "command": "npx",
            "args": ["@playwright/mcp@latest"]
        }
    }
}

client = MCPClient.from_dict(config)
agent = MCPAgent(
    llm=llm, 
    client=client,
    use_server_manager=True  # Enable smart server selection
)

result = await agent.run(
    "Search for a place in Barcelona on Airbnb, "
    "then find nearby restaurants using Google"
)