An MCP server that connects to OPC UA-enabled industrial systems, allowing AI agents to monitor, analyze, and control operational data in real time.

This project is ideal for developers and engineers looking to bridge AI-driven workflows with industrial automation systems.

• Read OPC UA Nodes: Retrieve real-time values from industrial devices.
• Write to OPC UA Nodes: Control devices by writing values to specified nodes.
• Seamless Integration: Works with MCP clients like Claude Desktop for natural language interaction.

The server exposes two tools:

• read_opcua_node:

  • Description: Read the value of a specific OPC UA node.
  • Parameters:
    • node_id (str): OPC UA node ID (e.g., ns=2;i=2).
  • Returns: A string with the node ID and its value (e.g., "Node ns=2;i=2 value: 42").

• write_opcua_node:

  • Description: Write a value to a specific OPC UA node.
  • Parameters:
    • node_id (str): OPC UA node ID (e.g., ns=2;i=3).
    • value (str): Value to write (converted based on node type).
  • Returns: A success or error message (e.g., "Successfully wrote 100 to node ns=2;i=3").

• "What’s the value of node ns=2;i=2?" → Returns the current value.
• "Set node ns=2;i=3 to 100." → Writes 100 to the node.

• Python 3.10 or higher
• An OPC UA server (e.g., a simulator or real industrial device)

Clone the repository and install the required Python packages:

git clone https://github.com/kukapay/opcua-mcp.git
cd opcua-mcp
pip install asyncua mcp[cli]

{
 "mcpServers": {
   "opcua-mcp": {
     "command": "python",
     "args": ["path/to/opcua_mcp/main.py"],
     "env": {
        "OPCUA_SERVER_URL": "your-opc-ua-server-url"
     }
   }
 }
}

This project is licensed under the MIT License. See the LICENSE file for details.