DocSentinel: MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports

by arthurpanhku · MCP Server · ★ 90

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install DocSentinel

git clone https://github.com/arthurpanhku/DocSentinel.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars90
Forks10
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score66/100
Open Issues24
Last Updated2026-10-28
Created2026-03-06
Platformsmcp, python
Est. Tokens~18k

About DocSentinel

English Русский DocSentinel AI-powered SSDLC platform — Secure your software from requirements to operations <img src="https://img.shields.io/badge/

Compatible Skills

These tools work well together with DocSentinel for enhanced workflows:

  • ai-chatkit — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (54%)
  • InsightFlow — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • agent-second-brain — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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