NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol
Quick Take
NIMO Controller is an MCP-based orchestrator for self-driving laboratories, enhancing accessibility for both humans and AI.
Key Points
- Introduces a visual programming interface for experimental workflows.
- Supports both human users and AI agents through a unified MCP backend.
- Demonstrated with a color-matching self-driving laboratory case study.
📖 Reader Mode
~2 min readAbstract:Self-driving laboratories (SDLs) have attracted increasing attention as a means of accelerating scientific discovery; however, developing SDL software remains technically demanding. To improve accessibility, orchestration software frameworks have been proposed to coordinate SDL components. Nevertheless, existing frameworks are primarily designed for human interaction and do not provide standardized interfaces suitable for AI agents. In this work, we propose an SDL software architecture based on the Model Context Protocol (MCP), in which all SDL functionalities are exposed through MCP servers. Following this design principle, we introduce an MCP-based SDL orchestrator, named NIMO Controller. It provides a visual programming interface automatically generated through MCP-based tool discovery, allowing human users to design experimental workflows without writing code. The same MCP backend can also be accessed by AI agents, providing a unified interface for both human users and AI agents. We demonstrate the proposed system through a case study on a color-matching SDL. The results validate the usability of the proposed MCP-based SDL architecture.
| Comments: | 9 pages, 4 figures |
| Subjects: | Artificial Intelligence (cs.AI); Materials Science (cond-mat.mtrl-sci); Robotics (cs.RO) |
| Cite as: | arXiv:2605.15227 [cs.AI] |
| (or arXiv:2605.15227v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2605.15227 arXiv-issued DOI via DataCite |
Submission history
From: Naruki Yoshikawa [view email]
[v1]
Wed, 13 May 2026 14:25:45 UTC (2,809 KB)
— Originally published at arxiv.org
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