AI assistants can decompose multi-step workflows, but they do not natively speak industrial protocols such as Modbus, MQTT/Sparkplug B, or OPC UA, so this paper presents INDUSTRICONNECT, a prototype suite of Model Context Protocol (MCP) adapters that expose industrial operations as schema-discoverable AI tools while preserving protocol-specific connectivity and safety controls; the system uses a common response envelope and a mock-first workflow so adapter behavior can be exercised locally before connecting to plant equipment, and a deterministic benchmark covering normal, fault-injected, stress, and recovery scenarios evaluates the flagship adapters, comprising 870 runs (480 normal, 210 fault-injected, 120 stress, 60 recovery trials) and 2820 tool calls across 7 fault scenarios and 12 stress scenarios, where the normal suite achieved full success, the fault suite confirmed structured error handling with adapter-level uint16 range validation, the stress suite identified concurrency boundaries, and same-session recovery after endpoint restart is demonstrated for all three protocols, with results providing evidence spanning adapter correctness, concurrency behavior, and structured error handling for AI-assisted industrial operations.

翻译：AI助手能够分解多步骤工作流，但无法原生支持Modbus、MQTT/Sparkplug B或OPC UA等工业协议。为此，本文提出INDUSTRICONNECT——一套模型上下文协议（MCP）适配器原型套件，可将工业操作暴露为模式可发现的AI工具，同时保留协议特定的连接性与安全控制。该系统采用通用响应封装与模拟优先工作流，使得适配器行为可在连接工厂设备前于本地完成测试。通过涵盖正常、故障注入、压力与恢复场景的确定性基准测试，对旗舰适配器进行评估：共包含870次运行（480次正常、210次故障注入、120次压力、60次恢复试验）及2820次工具调用，覆盖7个故障场景与12个压力场景。其中，正常套件实现完全成功，故障套件验证了结构化错误处理（适配器级uint16范围验证），压力套件揭示了并发边界，三种协议均演示了端点重启后的同会话恢复能力。实验结果从适配器正确性、并发行为及结构化错误处理三个维度，为AI辅助工业操作提供了实证依据。