Democratizing AI scientists using ToolUniverse
Authors: name: Shanghua Gao, name: Richard Zhu, name: Pengwei Sui, name: Zhenglun Kong, name: Sufian Aldogom, name: Yepeng Huang, name: Ayush Noori, name: Reza Shamji, name: Krishna Parvataneni, name: Theodoros Tsiligkaridis, name: Marinka Zitnik
Organization: Harvard University

AI scientists are emerging computational systems that serve as collaborative
partners in discovery. These systems remain difficult to build because they are
bespoke, tied to rigid workflows, and lack shared environments that unify
tools, data, and analyses into a common ecosystem. In omics, unified ecosystems
have transformed research by enabling interoperability, reuse, and
community-driven development; AI scientists require comparable infrastructure.
We present ToolUniverse, an ecosystem for building AI scientists from any
language or reasoning model, whether open or closed. TOOLUNIVERSE standardizes
how AI scientists identify and call tools, integrating more than 600 machine
learning models, datasets, APIs, and scientific packages for data analysis,
knowledge retrieval, and experimental design. It automatically refines tool
interfaces for correct use by AI scientists, creates new tools from natural
language descriptions, iteratively optimizes tool specifications, and composes
tools into agentic workflows. In a case study of hypercholesterolemia,
ToolUniverse was used to create an AI scientist to identify a potent analog of
a drug with favorable predicted properties. The open-source ToolUniverse is
available at https://aiscientist.tools.