No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by FROWNINGdev · MCP Server · ★ 76
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is django-orm-lens safe to install? View the security audit →
English · Русский · Español · 中文 Django ORM Lens The schema intelligence layer for Django. Your entire model graph — live in your editor sidebar, gating your CI, and answering your AI agent over MCP. All from static parsing: no database, no , no working venv. Replaces: + + hand-drawn ER diagrams + grep archaeology. [](https://github.com/F
| Stars | 76 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 62.9250051504367/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-28 |
| Created | 2026-07-12 |
| Platforms | cli, mcp, python, vscode |
| Est. Tokens | ~25k |
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django-orm-lens is Django ER diagrams, N+1 detection, schema drift & migration-risk linting — in VS Code, a CLI and an MCP server. Static analysis: no database, no django.setup(). Free & MIT.. It is categorized as a MCP Server with 76 GitHub stars.
django-orm-lens is primarily written in Python. It covers topics such as ai-agents, aider, code-navigation.
You can find installation instructions and usage details in the django-orm-lens GitHub repository at github.com/FROWNINGdev/django-orm-lens. The project has 76 stars and 12 forks, indicating an active community.
django-orm-lens is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to django-orm-lens on Agent Skills Hub include OpenLore, django-ninja-aio-crud, google-analytics-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: