论文概要
研究领域: ML 作者: Naruki Yoshikawa, Ryo Tamura 发布时间: 2025-05-15 arXiv: 2505.10884
中文摘要
自动驾驶实验室（SDL）作为加速科学发现的手段吸引了越来越多的关注；然而，开发SDL软件在技术上仍然具有挑战性。为提高可访问性，已提出编排软件框架来协调SDL组件。尽管如此，现有框架主要面向人类交互设计，未提供适合AI智能体的标准化接口。在本工作中，我们提出一种基于模型上下文协议（MCP）的SDL软件架构，其中所有SDL功能都通过MCP服务器暴露。遵循这一设计原则，我们引入一个基于MCP的SDL编排器，名为NIMO Controller。它通过基于MCP的工具发现自动生成可视化编程界面，允许人类用户在不编写代码的情况下设计实验工作流。同样的MCP后端也可以被AI智能体访问，为人类用户和AI智能体提供统一接口。我们通过一个颜色匹配SDL的案例研究展示了所提出的系统。结果验证了所提出的基于MCP的SDL架构的可用性。
原文摘要
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,...
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