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arxiv 2506.23474 v1 pith:UWLFOSGL submitted 2025-06-30 cs.CR

A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis

classification cs.CR
keywords ecosystemmcpcorpusinterfacecontextdatadatasetgithublarge-scale
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The Model Context Protocol (MCP) has recently emerged as a standardized interface for connecting language models with external tools and data. As the ecosystem rapidly expands, the lack of a structured, comprehensive view of existing MCP artifacts presents challenges for research. To bridge this gap, we introduce MCPCorpus, a large-scale dataset containing around 14K MCP servers and 300 MCP clients. Each artifact is annotated with 20+ normalized attributes capturing its identity, interface configuration, GitHub activity, and metadata. MCPCorpus provides a reproducible snapshot of the real-world MCP ecosystem, enabling studies of adoption trends, ecosystem health, and implementation diversity. To keep pace with the rapid evolution of the MCP ecosystem, we provide utility tools for automated data synchronization, normalization, and inspection. Furthermore, to support efficient exploration and exploitation, we release a lightweight web-based search interface. MCPCorpus is publicly available at: https://github.com/Snakinya/MCPCorpus.

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Cited by 1 Pith paper

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  1. Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions

    cs.CR 2026-07 conditional novelty 6.0

    SPELLSMITH mitigates taint-style vulnerabilities in MCP servers by augmenting tool descriptions with security constraints and adding LLM self-reflection before tool invocation, reducing attack success rates to near zero.