73
/100
B
◉ Complete 5⁄4
local_lense
A local RAG-powered documentation search system that uses vector embeddings and Qdrant to enable semantic search across markdown, HTML, and other file formats. It provides an MCP interface for AI tools like Cursor to intelligently query and retrieve information from local knowledge bases.
Qdrant
Glama
Complete visibility
— 5/4 applicable dimensions scored
✓ Schema Quality
✓ Protocol
— Reliability
✓ Docs & Maintenance
✓ Security Hygiene
✓ Schema Interpretability
Schema Quality
66
42% weight
Protocol Compliance
N/A
Local server
Reliability
N/A
Local server
Docs & Maintenance
49
25% weight
Security Hygiene
95
33% weight
Schema Interpretability
96
15% weight
Score History
Category Trends
Static Analysis
| Metric | Score | Rating |
|---|---|---|
| Schema Completeness | 50 | Fair |
| Description Quality | 90 | Good |
| Documentation Coverage | 47 | Fair |
| Maintenance Pulse | 40 | Fair |
| Dependency Health | 55 | Fair |
| License Clarity | 100 | Good |
| Version Hygiene | — | Poor |
Analyzed 1 month ago
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