by apisec-inc · MCP Server · ★ 165
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/apisec-inc/mcp-audit.git
docker run -v $(pwd):/scan mcp-audit scanTaken from the project's README on GitHub.
Flagged: spawns subprocesses. 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.
| Stars | 165 |
| Forks | 45 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 77/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-18 |
| Created | 2025-12-12 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~16k |
MCP Audit See what your AI agents can access - before they go live. Web App CLI Quick Start What It Does MCP Audit scans your AI development tools (Claude Desktop, Cursor, VS Code) and reveals: Secrets - Exposed API keys, tokens, database passwords APIs - Every endpoint your AI agents connect to AI Models - Which LLMs are configured (GPT-4, Claude, Llama) Risk Flags - Shell access, filesystem...
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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: