OPC UA MCP Server – Bridging Industrial Automation and AI

The OPC UA MCP Server is a ready‑made bridge that lets conversational AI assistants, such as Claude, interact directly with industrial OPC UA (Open Platform Communications Unified Architecture) servers. By exposing a set of high‑level tools—reading, writing, browsing nodes and invoking methods—the server eliminates the need for custom integration code. Developers can now ask natural‑language questions and trigger real‑time control or monitoring actions on factory equipment, all through the same conversational interface used for everyday queries.

Why It Matters

Industrial control systems traditionally rely on proprietary SCADA or custom APIs that are difficult to expose securely to AI agents. The OPC UA MCP Server solves this by standardizing the interaction through the Model Context Protocol, which is already supported by leading AI assistants. This means a single, well‑documented tool set can be reused across multiple factories, regardless of the underlying OPC UA implementation. It also provides automatic type detection and conversion, reducing the cognitive load on developers who would otherwise have to map complex OPC UA data types manually.

Core Features

• Node‑level CRUD – and let the assistant fetch or set values on any node by its ID, with automatic handling of data types such as integers, booleans, and strings.
• Batch Operations – Read or write multiple nodes in a single call, improving efficiency for large‑scale monitoring tasks.
• Method Invocation – enables execution of OPC UA server methods, such as starting a batch process or resetting alarms.
• Discovery – and node‑child browsing expose the entire address space, allowing the assistant to present a comprehensive inventory of sensors and actuators.
• Cross‑Language Support – The server is available in both Python (FastMCP) and TypeScript (Node‑OPCUA), giving teams flexibility in deployment environments.

Real‑World Use Cases

• Production Line Control – “Start production on line 1 at 100 units/hour” triggers a write operation that sets the conveyor speed and initiates the production routine.
• Safety & Compliance – “Show all alarm states” retrieves current fault conditions, enabling the assistant to alert operators or trigger automated shutdowns.
• Predictive Maintenance – Continuous reading of temperature and vibration sensors feeds into AI models that forecast component wear.
• Energy Management – “Get energy consumption readings” lets the assistant analyze power usage trends and suggest optimization strategies.

Integration into AI Workflows

When a user asks a question, the assistant parses intent and selects the appropriate MCP tool. The tool call is serialized over STDIO, executed by the server, and the result is returned as a natural‑language response. Because all interactions are stateless and JSON‑based, the server can be deployed behind a secure gateway or run locally on an edge device. This seamless flow means developers can focus on crafting conversational logic while the MCP server handles the heavy lifting of OPC UA communication.

Unique Advantages

• Zero Boilerplate – No custom SDKs or drivers are required; the server handles connection lifecycle and error reporting automatically.
• Consistent API Across Languages – Whether you’re using Python or TypeScript, the same tool names and parameters are available, simplifying cross‑team collaboration.
• Security by Design – The server operates over STDIO, making it easy to sandbox and audit; connection credentials can be injected at runtime.
• Extensibility – The tool set can be expanded to include additional OPC UA operations or custom method wrappers without changing the assistant’s core logic.

In summary, the OPC UA MCP Server empowers AI assistants to become genuine industrial co‑workers, turning natural language into precise control commands and real‑time data feeds with minimal developer effort.