mlsanityData to 14 Oct 2026

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

arXiv 2512.15144 ↗First posted 17 Dec 2025cs.CRcited by 4

On the map: LLM agents and tool use → Agent threats, guardrails and governance

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.

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.

Builds on

6 of 13 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025MCPGuard : Automatically Detecting Vulnerabilities in MCP Servers27 Oct
  2. 2025A Measurement Study of Model Context Protocol Ecosystem29 Sep
  3. 2025MCPXKIT: The Unified Toolkit for Analyzing Model Context Protocol Security18 Aug
  4. 2025MCPSecBench: A Systematic Security Benchmark and Playground for Testing Model Context Protocols17 Aug

Other references · 2

  1. 2025Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directionscited by 265
  2. 2025A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Codecited by 14

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Webcited by 4
  2. 2026From Skills to Talent: Organising Heterogeneous Agents as a Real-World Companycited by 1
  3. 2026TrustedARI: Towards Trust-Native Agentic Routing Infrastructure for Agentic AIcited by 1
  4. 2026AI Tool Discovery at Scale: All You Need is DNScited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Rethinking MCP Security: A Large-Scale Study of Runtime MCP Servers and Security Scanner Reliability
  2. 2026A Formal Security Framework for MCP-Based AI Agents: Threat Taxonomy, Verification Models, and Defense Mechanisms
  3. 2025MCP Guardian: A Security-First Layer for Safeguarding MCP-Based AI System
  4. 2026Don't believe everything you read: Understanding and Measuring MCP Behavior under Misleading Tool Descriptions
  5. 2025AgentBound: Securing Execution Boundaries of AI Agents
  6. 2025MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools
  7. 2025A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis
  8. 2026Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions