MCP-Flow

Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools

📄 Paper Url

🗓️ News

• 🎉 Apr 6, 2026 — We are happy to announce that MCP-Flow has been accepted to the Main Conference of ACL 2026!
• 🧠 Oct 28, 2025 — MCP-Flow is released on arXiv.
• 🛠️ Nov 10, 2025 — We open-source all the server configurations and tool information!
• 🛠️ Nov 28, 2025 — We open-source all the instruction-function call pairs and the testsets for evaluation inluding in-domain and OOD settings! The dataset is available at HuggingFace

📝 Introduction

MCP-Flow is an automated web-agent-driven pipeline for large-scale server discovery, data synthesis, and model training in the Model Context Protocol (MCP) ecosystem.

🌐 Key Features

• 🤖 Automated server collection from 6 major MCP marketplaces

  

• 📊 Extensive tool coverage: 1,166 real-world servers, 11,536 tools, and 68K+ instruction–function call pairs

  

• 🧩 Scale & diversity far beyond previous benchmarks

  

📂 Datasets

Category	Path	Description
🧠 Function calls & trajectories	./data/function_call/ & ./data/trajectory/	Example data; full datasets are released on HuggingFace
⚙️ MCP configurations	./data/mcp_config/	Configuration files for discovered servers
🧰 Tool information	./data/tools/	Tool descriptions and schema definitions
💻 Source code	./src/	Core scripts for server deployment
📲 Testset	./test_data on HuggingFace	Including in-domain and out-of-domain evaluation settings

🛠️ Installation

git clone https://github.com/<your-org>/MCP-Flow.git
cd MCP-Flow
pip install -r requirements.txt

🧾 Citation

If you find MCP-Flow useful in your research, please consider citing:

@misc{wang2025mcpflowfacilitatingllmagents,
      title={MCP-Flow: Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools}, 
      author={Wenhao Wang and Peizhi Niu and Zhao Xu and Zhaoyu Chen and Jian Du and Yaxin Du and Xianghe Pang and Keduan Huang and Yanfeng Wang and Qiang Yan and Siheng Chen},
      year={2025},
      eprint={2510.24284},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2510.24284}, 
}

📧 Contact

If you have any questions or encounter issues, feel free to open an issue or reach out to the authors directly:

📮 Email: 12321254@zju.edu.cn
💬 WeChat: