案例背景

需求痛点
企业需管理数百台跨地域网络设备（交换机/路由器），传统方式存在：

• 人工SSH登录效率低
• 脚本维护成本高（不同厂商CLI语法差异）
• 状态监控依赖独立监控系统

解决方案
通过MCP协议构建智能网络管控平台：

• 将设备操作封装为MCP工具
• 允许AI模型（如Claude）理解自然语言指令并触发操作
• 实现"语音/文字指令 → 自动执行"的闭环

---

架构设计

---

核心工具开发

1. 工具描述符定义 (network_tools.json)

[
  {
    "name": "batch_configure_devices",
    "description": "批量配置网络设备",
    "parameters": {
      "type": "object",
      "properties": {
        "device_ips": {"type": "array", "items": {"type": "string"}, "description": "设备IP列表"},
        "commands": {"type": "array", "items": {"type": "string"}, "description": "CLI命令序列"},
        "credential_id": {"type": "string", "description": "预存凭证标识符"}
      },
      "required": ["device_ips", "commands"]
    }
  },
  {
    "name": "check_device_status",
    "description": "检查设备健康状态",
    "parameters": {
      "type": "object",
      "properties": {
        "device_ip": {"type": "string"},
        "metrics": {"type": "array", "items": {"enum": ["cpu", "memory", "interface"]}}
      }
    }
  }
]

2. MCP Server实现（Python示例）

from netmiko import ConnectHandler
from mcp_server import McpServer

app = FastAPI()
server = McpServer(app)

# 连接池管理（示例简化版）
devices = {
    "192.168.1.1": {"device_type": "cisco_ios", "credential": "admin:password"},
    "192.168.1.2": {"device_type": "huawei", "credential": "admin:huawei@123"}
}

@server.tool("batch_configure_devices")
async def batch_config(device_ips: list, commands: list, credential_id: str):
    results = {}
    for ip in device_ips:
        conn = ConnectHandler(
            ip=ip,
            username=devices[ip]["credential"].split(':')[0],
            password=devices[ip]["credential"].split(':')[1],
            device_type=devices[ip]["device_type"]
        )
        output = conn.send_config_set(commands)
        results[ip] = output
    return {"success": True, "details": results}

@server.tool("check_device_status")
async def check_status(device_ip: str, metrics: list):
    status = {}
    if "cpu" in metrics:
        status["cpu"] = get_cpu_usage(device_ip)  # 实现SNMP查询
    if "memory" in metrics:
        status["memory"] = get_memory_usage(device_ip)
    return status

---

典型交互流程

场景：批量配置OSPF路由

1. 用户指令
   “为北京机房的所有核心交换机（IP段192.168.10.1-10）配置OSPF Area 0，进程号100”

2. AI响应

   {
     "method": "batch_configure_devices",
     "params": {
       "device_ips": ["192.168.10.1", ..., "192.168.10.10"],
       "commands": [
         "router ospf 100",
         "network 192.168.0.0 0.0.255.255 area 0"
       ]
     }
   }
   

3. 执行结果

   {
     "192.168.10.1": "配置成功，耗时2.3秒",
     "192.168.10.2": "Error: 设备未响应",
     ...
   }
   

---

安全增强设计

1. 凭证管理

   • 使用Vault服务替代明文存储
   • MCP请求需携带JWT令牌

   @server.auth_handler
   async def validate_token(token: str):
       return auth_service.verify(token)
   

2. 操作审计

   @server.tool_usage_hook
   async def audit_log(context: dict):
       write_to_elasticsearch({
           "user": context["user"],
           "tool": context["method"],
           "params": context["params"]
       })
   

---

性能优化方案

1. 并发控制

   from fastapi.concurrency import run_in_threadpool
   
   @server.tool("batch_configure_devices")
   async def batch_config(...):
       # 使用线程池并发执行
       loop = asyncio.get_event_loop()
       tasks = [loop.run_in_executor(None, configure_single_device, ip) for ip in device_ips]
       await asyncio.gather(*tasks)
   

2. 厂商适配层

   def send_config_set(conn, commands):
       if conn.device_type == "huawei":
           return huawei_special_handler(commands)  # 处理华为设备差异
       return conn.send_config_set(commands)
   

---

部署架构建议

通过该方案，企业可将网络运维效率提升300%以上，同时通过自然语言交互降低操作门槛。