Large Language Model (LLM)-based agent systems are increasingly being used for scientific discovery, yet their practical capability remains constrained by a narrow and manually curated tool layer. Much scientific computational capability already exists in open-source repositories, software packages and APIs, but these resources remain difficult to standardize, operationalize and invoke reliably. Here we present ToolRosetta, a framework that equips LLM-based agent systems with scalable, open-world computational access by automatically transforming heterogeneous computational programs into validated, callable tools. ToolRosetta integrates repository retrieval, tool standardization, execution testing, iterative repair and security-aware governance. Across 122 GitHub repositories spanning 35 subdisciplines in 6 domains, ToolRosetta standardizes 1,580 callable tools. These tools support an average verified task success rate of 84.0\% across domains and substantially enhance existing agentic AI systems, including OpenClaw, particularly on out-of-distribution tasks beyond fixed curated tool inventories.

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