Enables AI assistants to index and search codebases using semantic search powered by multiple embedding providers (OpenAI, VoyageAI, Gemini, Ollama) and vector database storage.
Enables semantic search across indexed documents using vector embeddings. Index GitHub repositories and URLs to perform natural language queries with AI-enhanced contextual results.
Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.
Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache and workspace management, status checks, and latest package-version lookup.
Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache management, workspace switching, status checks, and package version lookup. It supports incremental and progressive indexing with configurable embedding dimensions to find relevant code even when terminology differs.