Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by iktok90-design · MCP Server · ★ 75
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🔒 Is ai-smart-contract-auditor safe to install? View the security audit →
🔐 AuditSentry — AI-Powered Smart Contract Auditor AI-driven security analysis for Solidity & Vyper smart contracts. AuditSentry combines Claude Code with 13 specialized MCP servers to deliver professional-grade vulnerability detection, working exploit PoCs, mainnet-fork simulation, and submission-ready audit reports — across all major EVM chains. 🔍 AI Audit 🏷️ On-Chain Certificates 🔥 Real-World Vulnerability Detection AuditSentry has successfully identified critical and high-severity vulnerabilities across DeFi protocols, including vulnerability patterns that consistently bypass traditional static analysis tools: ❌ Misse
| Stars | 75 |
| Forks | 2 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 54.6479194464414/100 |
| Open Issues | 3 |
| Last Updated | 2026-08-10 |
| Created | 2026-08-10 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~13k |
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ai-smart-contract-auditor is AuditSentry — AI-powered smart contract security auditor for Claude Code. Automated vulnerability detection, exploit PoCs, mainnet-fork simulation, and professional audit reports for Solidity & Vyper . It is categorized as a MCP Server with 75 GitHub stars.
ai-smart-contract-auditor is primarily written in JavaScript. It covers topics such as ai, audit, claude-code.
You can find installation instructions and usage details in the ai-smart-contract-auditor GitHub repository at github.com/iktok90-design/ai-smart-contract-auditor. The project has 75 stars and 2 forks, indicating an active community.
ai-smart-contract-auditor is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-smart-contract-auditor on Agent Skills Hub include slither-mcp, free-crypto-news, claude-code-owasp. 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: