# MCPZoo: A Large-Scale Dataset of Runnable Model Context Protocol Servers for AI Agent

arXiv: https://arxiv.org/abs/2512.15144 · HTML: https://mlsanity.com/paper/2512.15144/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 6 of its 13 references that are in the map.
- First posted on arXiv 17 Dec 2025.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 6 of 6)

- [Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions](https://mlsanity.com/paper/2503.23278/) (2025)
- [MCPSecBench: A Systematic Security Benchmark and Playground for Testing Model Context Protocols](https://mlsanity.com/paper/2508.13220/) (2025)
- [MCPXKIT: The Unified Toolkit for Analyzing Model Context Protocol Security](https://mlsanity.com/paper/2508.12538/) (2025)
- [A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code](https://mlsanity.com/paper/2508.18106/) (2025)
- [MCPGuard : Automatically Detecting Vulnerabilities in MCP Servers](https://mlsanity.com/paper/2510.23673/) (2025)
- [A Measurement Study of Model Context Protocol Ecosystem](https://mlsanity.com/paper/2509.25292/) (2025)

## Built on by (most cited first, 4 of 4)

- [Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web](https://mlsanity.com/paper/2604.02334/) (2026)
- [From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company](https://mlsanity.com/paper/2604.22446/) (2026)
- [TrustedARI: Towards Trust-Native Agentic Routing Infrastructure for Agentic AI](https://mlsanity.com/paper/2606.15822/) (2026)
- [AI Tool Discovery at Scale: All You Need is DNS](https://mlsanity.com/paper/2607.18242/) (2026)

## Abstract (arXiv)

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.