Enables semantic code search across codebases using Qdrant vector database and OpenAI embeddings, allowing users to find code by meaning rather than just keywords through natural language queries.
Enables semantic search across your codebase using Google's Gemini embeddings and Qdrant Cloud vector storage. Supports 15+ programming languages with smart code chunking and real-time file change monitoring.
Provides semantic search capabilities using Qdrant vector database with multiple embedding providers, including hybrid search, code indexing, and git history search. Adds optional time-based recency scoring to search results.
Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.
Enables semantic code search for AI assistants by indexing codebases with embeddings and Tree-sitter, returning relevant snippets via natural language queries.