Code2MCP: Transforming Code Repositories into MCP Services

Chaoqian Ouyang, Ling Yue, Shimin Di, Libin Zheng, Shaowu Pan, Min-Ling Zhang

Keywords: Agent, Model Context Protocol, Large Language Model, Multi-Agent, MCP, Github

TL;DR: Our framework unlocks the vast potential of open-source code by autonomously transforming any GitHub repository into a ready-to-use MCP service, eliminating the critical bottleneck in AI tool integration.

Abstract: The Model Context Protocol (MCP) aims to create a standard for how Large Language Models use tools. However, most current research focuses on selecting tools from an existing pool. A more fundamental, yet largely overlooked, problem is how to populate this pool by converting the vast number of existing software projects into MCP-compatible services. To bridge this gap, we introduce Code2MCP, an agent-based framework that automatically transforms a GitHub repository into a functional MCP service with minimal human intervention. Code2MCP employs a multi-agent workflow for code analysis, environment setup, tool function design, and service generation, enhanced by a self-correcting loop to ensure reliability. We demonstrate that Code2MCP successfully transforms open-source computing libraries in scientific fields such as bioinformatics, mathematics, and fluid dynamics that are not available in existing MCP servers. By providing a novel automated pathway to unlock GitHub, the world's largest code repository, for the MCP ecosystem, Code2MCP serves as a catalyst to significantly accelerate the protocol's adoption and practical application. The code is public at https://github.com/DEFENSE-SEU/Code2MCP.

Archival Option: The authors of this submission do *not* want it to appear in the archival proceedings.

Submission Number: 94