ToolRosetta：通过自动化工具标准化桥接开源仓库与大型语言模型智能体

摘要

代码复用与调用仍面临高成本与低可靠性问题，这主要源于实用工具大多嵌入异构代码库且缺乏标准化可执行接口。尽管大语言模型（LLMs）和基于模型上下文协议（MCP）的工具调用框架支持自然语言任务执行，但现有方法严重依赖人工工具整理与标准化，从根本上制约了可扩展性。本文提出ToolRosetta统一框架，能自动将开源代码库和API转换为符合MCP标准的工具，供LLMs可靠调用。面对用户任务时，ToolRosetta可自主规划工具链、识别相关代码库，并将其转化为可执行的MCP服务，实现端到端任务完成且无需过多人工干预。该框架还集成安全检测层以降低执行任意代码的固有风险。跨学科大规模实验表明，ToolRosetta能自动标准化大量开源工具，显著减少代码复现与部署的人力成本。值得注意的是，通过无缝集成专业开源工具，基于ToolRosetta的智能体在任务完成效果上持续优于商用LLMs及现有智能体系统。

English

Reusing and invoking existing code remains costly and unreliable, as most practical tools are embedded in heterogeneous code repositories and lack standardized, executable interfaces. Although large language models (LLMs) and Model Context Protocol (MCP)-based tool invocation frameworks enable natural language task execution, current approaches rely heavily on manual tool curation and standardization, which fundamentally limits scalability. In this paper, we propose ToolRosetta, a unified framework that automatically translates open-source code repositories and APIs into MCP-compatible tools that can be reliably invoked by LLMs. Given a user task, ToolRosetta autonomously plans toolchains, identifies relevant codebases, and converts them into executable MCP services, enabling end-to-end task completion with minimal human intervention. In addition, ToolRosetta incorporates a security inspection layer to mitigate risks inherent in executing arbitrary code. Extensive experiments across diverse scientific domains demonstrate that ToolRosetta can automatically standardize a large number of open-source tools and reduce the human effort required for code reproduction and deployment. Notably, by seamlessly leveraging specialized open-source tools, ToolRosetta-powered agents consistently improve task completion performance compared to commercial LLMs and existing agent systems.

ToolRosetta：通过自动化工具标准化桥接开源仓库与大型语言模型智能体

ToolRosetta: Bridging Open-Source Repositories and Large Language Model Agents through Automated Tool Standardization

摘要

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