Enables semantic code search across codebases with automatic incremental indexing. Searches return relevant code snippets with file paths and line numbers based on natural language queries.
Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.
Enables semantic search of project documentation using hybrid vector and full-text search with fast and deep query modes for immediate results or complex multi-round synthesis.
Enables semantic code search across projects using AI embeddings to find code by meaning rather than just text matching. Provides fast intelligent search, symbol analysis, and code similarity detection with multi-language support.
Enables semantic search across indexed documents using vector embeddings. Index GitHub repositories and URLs to perform natural language queries with AI-enhanced contextual results.
Provides intelligent semantic code search using local AI embeddings, enabling natural language queries to find relevant code by meaning rather than exact keywords. Indexes codebases in the background with smart project detection and privacy-first local processing.