CrewAI 集成

將CrewAI多智能體團隊連接到TalorData MCP服務器，可以使用託管端點或自託管模式進行實时Web數據訪問。

託管 MCP

1

獲取您的 API 令牌

• 前往 SERP API-API Token 創建API Token

• 複製您的API Token（格式如下：sk_7qBRe***************************）

2

配寘您的 MCP 服務器

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import os


server_params = {
    "url": "https://mcp.talordata.net/API_TOKEN/mcp",
    "transport": "http"
}

try:
    with MCPServerAdapter(server_params) as mcp_tools:
        print(f"Available tools: {[tool.name for tool in mcp_tools]}")
        
        my_agent = Agent(
            role="Web Scraping Specialist",
            goal="Extract data from websites using TalorData tools",
            backstory="I am an expert at web scraping and data extraction using MCP tools.",
            tools=mcp_tools,
            verbose=True,
            llm="gpt-4o-mini",
        )
        
        task = Task(
            description="Search for flights from New York to San Francisco and provide a summary of what you found. Use the search_engine tool to find flight information and return the results in a clear format.",
            expected_output="A clear summary of available flights from New York to San Francisco, including key details like airlines, times, and prices if available.",
            agent=my_agent
        )
        
        crew = Crew(
            agents=[my_agent],
            tasks=[task],
            verbose=True
        )
        
        result = crew.kickoff()
        print("\n=== RESULT ===")
        print(result)
        
except Exception as e:
    print(f"Error connecting to MCP server: {e}")
    print("Make sure you have:")
    print("1. Set your TALOR_DATA_API_KEY environment variable")
    print("2. Installed the TalorData MCP server: npm install -g @talor_data/ai/mcp-server-talor-data")
    print("3. Have Node.js installed on your system")

3

測試一下是否有效

• 運行CrewAI腳本並執行航班搜索任務

• 代理將使用TalorData工具搜索航班信息

• 您應該會看到包含班機詳情的結果。

4

監控使用情况

在 TalorData SERP API-使用記錄 中查看您的 API 使用情况。