by raw-labs · MCP Server · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install mxcp
git clone https://github.com/raw-labs/mxcp.git
Taken from the project's README on GitHub.
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.
| Stars | 68 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 61/100 |
| Open Issues | 45 |
| Last Updated | 2026-06-30 |
| Created | 2025-05-21 |
| Platforms | claude-code, cli, mcp, python |
| Est. Tokens | ~19k |
MXCP: Enterprise-Grade MCP Framework for AI Applications The structured methodology for building production-ready MCP servers with enterprise security, data quality, and comprehensive testing 🚀 What Makes MXCP Different? MXCP isn't just another MCP implementation - it's a complete methodology for building production AI applications the right way: The Production-Ready Approach 📊 Data Modeling...
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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: