by vintasoftware · MCP Server · ★ 114
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
uv pip install django-ai-boost
pip install django-ai-boostTaken 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 | 114 |
| Forks | 5 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76/100 |
| Last Updated | 2026-07-31 |
| Created | 2025-10-17 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~19k |
Django AI Boost A Model Context Protocol (MCP) server for developing Django applications, inspired by Laravel Boost. This server exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.
These tools work well together with django-ai-boost for enhanced workflows:
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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: