No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by arthurpanhku · MCP Server · ★ 87
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is DocSentinel safe to install? View the security audit →
English Русский DocSentinel AI-powered SSDLC platform — Secure your software from requirements to operations <img src="https://img.shields.io/badge/
| Stars | 87 |
| Forks | 9 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.6788036621408/100 |
| Open Issues | 21 |
| Last Updated | 2026-09-18 |
| Created | 2026-03-06 |
| Platforms | mcp, python |
| Est. Tokens | ~18k |
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DocSentinel is MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations.. It is categorized as a MCP Server with 87 GitHub stars.
DocSentinel is primarily written in Python. It covers topics such as ai-agent, compliance, document-parsing.
You can find installation instructions and usage details in the DocSentinel GitHub repository at github.com/arthurpanhku/DocSentinel. The project has 87 stars and 9 forks, indicating an active community.
DocSentinel is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to DocSentinel on Agent Skills Hub include orchestkit, c4-genai-suite, pdfmux. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: