mlsanityData to 7 Oct 2026

Code2MCP: Transforming Code Repositories into MCP Services

arXiv 2509.05941 ↗First posted 7 Sep 2025cs.SE cs.LG cs.MAcited by 10

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 29 of its 62 references that are in the map. First posted on arXiv 7 Sep 2025.

Builds on

29 of 62 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System7 May
  2. 2025LLM Agents Making Agent Tools17 Feb
  3. 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future5 Aug
  4. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges14 Jan

Other references · 25

  1. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  3. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  4. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  5. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  6. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
  7. 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,302
  8. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,173
  9. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  10. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMscited by 574
  11. 2025Multi-Agent Collaboration Mechanisms: A Survey of LLMscited by 424
  12. 2024Understanding the planning of LLM agents: A surveycited by 414
13 more
  1. 2023Tool Learning with Foundation Modelscited by 302
  2. 2024Tool Learning with Large Language Models: A Surveycited by 221
  3. 2022TALM: Tool Augmented Language Modelscited by 197
  4. 2023TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIscited by 184
  5. 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
  6. 2023OpenAgents: An Open Platform for Language Agents in the Wildcited by 136
  7. 2025A Survey on Trustworthy LLM Agents: Threats and Countermeasurescited by 93
  8. 2025Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Serverscited by 62
  9. 2025SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integrationcited by 40
  10. 2024ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoningcited by 31
  11. 2025RAG-MCP: Mitigating Prompt Bloat in LLM Tool Selection via Retrieval-Augmented Generationcited by 26
  12. 2025RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solvingcited by 19
  13. 2025CSR-Bench: Benchmarking LLM Agents in Deployment of Computer Science Research Repositoriescited by 15

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 7.

10 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026ToolRosella: Translating Code Repositories into Standardized Tools for Scientific Agents
  2. 2026A Large-Scale Dataset of MCP Implementations on GitHub
  3. 2026ReCUBE: Evaluating Repository-Level Context Utilization in Code Generation
  4. 2026From Tool Orchestration to Code Execution: A Study of MCP Design Choices
  5. 2025NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents
  6. 2026An Empirical Study of Model Context Protocol Applications
  7. 2026A Two-Dimensional Study of the Model Context Protocol: Publication and Adoption
  8. 2026Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution