ToolRosetta: Bridging Open-Source Repositories and Large Language Model Agents through Automated Tool Standardization
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.
69c1ee58c105f45cb0481dcc
Shimin Di
69c1ee58c105f45cb0481dcd
Xujie Yuan
69c1ee58c105f45cb0481dce
Hanghui Guo
claimed_verified
2026-03-30T09:10:45.576Z
6565d27be67d21ed94bb9c8a
/avatars/e301f96e6637286030cc065cd9853ccb.svg
guohanghui
guohanghui
user
guohanghui
69c1ee58c105f45cb0481dcf
Chaoqian Ouyang
69c1ee58c105f45cb0481dd0
Zhangze Chen
69c1ee58c105f45cb0481dd1
Ling Yue
69c1ee58c105f45cb0481dd2
Libin Zheng
69c1ee58c105f45cb0481dd3
Jia Zhu
69c1ee58c105f45cb0481dd4
Shaowu Pan
69c1ee58c105f45cb0481dd5
Jian Yin
69c1ee58c105f45cb0481dd6
Min-Ling Zhang
69c1ee58c105f45cb0481dd7
Yong Rui
ToolRosetta: Bridging Open-Source Repositories and Large Language Model Agents through Automated Tool Standardization
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.