langgraph同时使用tool和mcp（三）

mcp job_info_tools

from app.config import comet_config
from sdk.langgraph.langgraph import AgentState
from service.mcpService import call_sse_tool


async def async_job_info_node(state: AgentState):
    """生成虚拟岗位信息节点"""
    print("--- 进入节点: Job Info ---")
    try:
        # 如果 job_info_node 是同步的，在线程池中执行
        user_id = state.get("userID")
        result =await job_info_func(user_id)
        state['job_info'] = result
        return state
    except Exception as e:
        print(f"❌ 岗位信息节点错误: {e}")
        state['error'] = f"岗位信息获取失败: {str(e)}"
        return state

async def job_info_func(userID: str) -> str:
    """根据用户提供的信息，生成一份虚拟的岗位"""
    print(f"--- TOOL: Calling job_info_func for userID: {userID} ---")
    params = {
        "name": "jobAgentSearch",  # ✅ 确保工具名正确
        "arguments": {"userId": userID, "message": "fff"},
    }
    result = await call_sse_tool(
        payload=params,
        auth_token=f"Bearer {comet_config['mcp_sk']}",
    )
    print("result", result)
    return result