62
/100
C
◉ Complete 5⁄5
Markdown RAG
A Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.
Google Gemini
Ollama
PostgreSQL
Glama
Complete visibility
— 5/5 applicable dimensions scored
✓ Schema Quality
✓ Protocol
— Reliability
✓ Docs & Maintenance
✓ Security Hygiene
✓ Schema Interpretability
Schema Quality
60
25% weight
Protocol Compliance
32
20% weight
Reliability
—
20% weight
Docs & Maintenance
36
15% weight
Security Hygiene
82
20% weight
Schema Interpretability
99
15% weight
Score History
Category Trends
30-Day Uptime
30 days ago
Today
Static Analysis
| Metric | Score | Rating |
|---|---|---|
| Schema Completeness | 60 | Fair |
| Description Quality | 60 | Fair |
| Documentation Coverage | 37 | Poor |
| Maintenance Pulse | 40 | Fair |
| Dependency Health | 55 | Fair |
| License Clarity | — | Poor |
| Version Hygiene | — | Poor |
Analyzed 1 month ago
Add this to your README to display your MCP Scoreboard grade:
