SciToolAgent: a knowledge-graph-driven scientific agent for multitool integration by Keyan Ding & Jing Yu & Junjie Huang & Yuchen Yang & Qiang Zhang & Huajun Chen instant download

SciToolAgent: a knowledge-graph-driven scientific agent for multitool integration by Keyan Ding & Jing Yu & Junjie Huang & Yuchen Yang & Qiang Zhang & Huajun Chen instant download

Scientifc research increasingly relies on specialized computational tools, yet efectively utilizing these tools requires substantial domain expertise. While large language models show promise in tool automation, they struggle to seamlessly integrate and orchestrate multiple tools for complex scientifc workfows. Here we present SciToolAgent, a large language model-powered agent that automates hundreds of scientifc tools across biology, chemistry and materials science. At its core, SciToolAgent leverages a scientifc tool knowledge graph that enables intelligent tool selection and execution through graph-based retrieval-augmented generation. The agent also incorporates a comprehensive safety-checking module to ensure responsible and ethical tool usage. Extensive evaluations on a curated benchmark demonstrate that SciToolAgent outperforms existing approaches. Case studies in protein engineering, chemical reactivity prediction, chemical synthesis and metal–organic framework screening further demonstrate SciToolAgent’s capability to automate complex scientifc workfows, making advanced research tools accessible to both experts and nonexperts.