VectorCodeLens

Semantic codebase analysis platform using vector embeddings and LLMs for intelligent code understanding.

Key Metrics

10x faster

Search Performance

Semantic search speed improvement

95%

Pattern Detection

Code pattern recognition accuracy

< 5 minutes

Setup Time

Time to deployment and value

99%

System Uptime

Availability with fallback systems

Understand code structure, patterns, and relationships using advanced LLM analysis and vector embeddings.

Ask questions about your codebase in plain English and get precise, contextual answers with code references.

Semantic search capabilities using Qdrant vector database for finding similar code patterns and concepts.

Graceful degradation ensuring core functionality works even when external AI services are unavailable.

Full Model Context Protocol implementation enabling seamless integration with AI development tools.

Structure-aware code segmentation that preserves context and relationships for better analysis accuracy.

TypeScript

Node.js

Qdrant Vector DB

Ollama

Claude API

Model Context Protocol

Vector Embeddings

LLM Integration