Model Context Protocol (MCP) enables agents to interact with external tools, yet empirical research on MCP is hindered by the lack of large-scale, accessible datasets. We present MCPZoo, the largest and most comprehensive dataset of MCP servers collected from multiple public sources, comprising 129,059 servers (56,053 distinct). MCPZoo includes 16,356 server instances that have been deployed and verified as runnable and interactable, supporting realistic experimentation beyond static analysis. The dataset provides unified metadata and access interfaces, enabling systematic exploration and interaction without manual deployment effort. MCPZoo is released as an open and accessible resource to support research on MCP-based systems and security analysis.
@article{arxiv.2512.15144,
title = {MCPZoo: A Large-Scale Dataset of Runnable Model Context Protocol Servers for AI Agent},
author = {Mengying Wu and Pei Chen and Geng Hong and Baichao An and Jinsong Chen and Binwang Wan and Xudong Pan and Jiarun Dai and Min Yang},
journal= {arXiv preprint arXiv:2512.15144},
year = {2025}
}