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import asyncio
from dedalus_labs import AsyncDedalus, DedalusRunner
from dotenv import load_dotenv

load_dotenv()

async def main():
    client = AsyncDedalus()
    runner = DedalusRunner(client)

    result = await runner.run(
        input="""I need to research the latest developments in AI agents for 2024.
        Please help me:
        1. Find recent news articles about AI agent breakthroughs
        2. Search for academic papers on multi-agent systems
        3. Look up startup companies working on AI agents
        4. Find GitHub repositories with popular agent frameworks
        5. Summarize the key trends and provide relevant links

        Focus on developments from the past 6 months.""",
        model="openai/gpt-4.1",
        mcp_servers=[
            "tsion/exa",        # 语义搜索引擎
            "windsor/brave-search-mcp"  # 注重隐私的网页搜索
        ]
    )

    print(f"Web Search Results:\n{result.final_output}")

if __name__ == "__main__":
    asyncio.run(main())
这个示例使用了多个搜索 MCP 服务器:
  • Exa MCP (tsion/exa):语义搜索,非常适合查找在概念层面相关的内容
  • Brave Search MCP (windsor/brave-search-mcp):面向当前事件和特定查询的、注重隐私的网页搜索
配合使用时,它们的覆盖范围比单独使用任一服务都更广——Exa 负责发现相关想法和内容,而 Brave 负责处理最新事件和具体查询。