Use Claude, GitHub Copilot and other coding agents to interact with existing Beckhoff TwinCAT projects through a structured engineering interface.
> TwinCAT_AI_Bridge --analyze POU_Main [INFO] Loading POU_Main.TcPOU... [INFO] Identifying logic structures: 1 State Machine, 3 Function Blocks. [REASONING] FB_MotorControl requires an updated Interlock signal. [SUGGESTION] Add 'bSafetyOK' to the transition logic in line 42. [OK] Ready to generate updated Structured Text.
Standard LLMs lack context for industrial automation structures. They struggle with POUs, Function Blocks, and the specific syntax of Structured Text within a Beckhoff environment.
Our MCP server translates complex TwinCAT 3 project files into a semantic structure that modern AI agents can comprehend and safely manipulate.
Install the plugin, then select the twincat agent.
claude /plugin marketplace add ricciolo/TwinCAT-Agent /plugin install twincat@twincat-plugins /agents
copilot plugin marketplace add ricciolo/TwinCAT-Agent copilot plugin install ricciolo/TwinCAT-Agent copilot /agent /allow-all on
For more information, visit the GitHub repository.
Agents analyze existing architecture to provide context-aware suggestions.
Automate repetitive structure creation, letting engineers focus on core logic.
Quickly locate variables, references, and dependencies across large codebases.
Search official documentation, look up symbols and types, and pull short excerpts as implementation references.
Enforce coding guidelines and naming conventions automatically.
All AI suggestions require human review before compilation.