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Control of legacy or industrial tools using natural language. Contribution to the 2025 LLM Hackathon for Applications in Materials Science & Chemistry.

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Natural Language Control of LabVIEW via IvoryOS

Python IvoryOS MCP License: MIT

This project demonstrates the integration of LabView automated tools into the self-driving lab software IvoryOS. The ability to control IvoryOS through Claude with an MCP interface allows to control the LabView software through natural language and easily integrate intelligent experimental design.

🚀 Quick Start

After running the 'main.py' file, the TCP server used to control the LabVIEW software can be started by clicking Devices → Chamber → Start Server. Then, the LabVIEW software needs to be started and the connection can be ensured by clicking Is Connected in the prior Ivory OS menu.

Afterwards, the LabVIEW software can be controlled either directly from the web interface or alternatively through natural language using the Claude interface:

Demonstration

🏗️ Architecture

Claude AI ◄──(MCP)──► IvoryOS Platform ◄──(TCP)──► LabVIEW Control

  • Claude AI: Natural language processing and intelligent control

  • MCP: Middleware Control Protocol for LLM-to-Ivory communication

  • IvoryOS: Automation platform with workflow management

  • TCP: Communication protocol layer connecting IvoryOS to LabVIEW

  • LabVIEW Control: Interface to the PVD system hardware

👥 Team

Developed during the LLM Hackathon for Applications in Materials Science & Chemistry as part of Ivory Zhang’s team in the Hein Lab at The University of British Columbia, this repository builds on the MCP server and provides an extended implementation.

📜 License

This project is licensed under the MIT License.
Note: LabVIEW itself and any NI toolkits remain subject to their own licensing terms.

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Control of legacy or industrial tools using natural language. Contribution to the 2025 LLM Hackathon for Applications in Materials Science & Chemistry.

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