Flagged: reads sensitive env vars. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by PV-Bhat · MCP Server · ★ 502
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is vibe-check-mcp-server safe to install? View the security audit →
Vibe Check MCP This project is in maintenance mode. Active feature development has ended; only maintenance patches (security and bug fixes) are published. v2.8.1 is the latest maintenance release. The server remains fully functional. Community forks and contributions are welcome under the MIT license. KISS overzealous agents goodbye. Plug & play agent oversight tool. Based on research: In our study agents calling Vibe Check improved success +27% and halved harmful actions -41% <img src="https://img.shields.io/badge/PulseMCP-Most%20Popular%20(Oct 2025)-0b7285?style=flat-square" alt="PulseMCP: Most Pop
| Stars | 502 |
| Forks | 67 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.0602942252868/100 |
| Last Updated | 2026-08-20 |
| Created | 2025-03-22 |
| Platforms | mcp, node |
| Est. Tokens | ~18k |
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vibe-check-mcp-server is Vibe Check is a tool that provides mentor-like feedback to AI Agents, preventing tunnel-vision, over-engineering and reasoning lock-in for complex and long-horizon agent workflows. KISS your over-eage. It is categorized as a MCP Server with 502 GitHub stars.
vibe-check-mcp-server is primarily written in TypeScript. It covers topics such as agentic-ai, agentic-workflow, ai-agents.
You can find installation instructions and usage details in the vibe-check-mcp-server GitHub repository at github.com/PV-Bhat/vibe-check-mcp-server. The project has 502 stars and 67 forks, indicating an active community.
vibe-check-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to vibe-check-mcp-server on Agent Skills Hub include mcp-memory-service, concierge, mcp. 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: