Clear the embeddings cache to resolve corruption issues or prepare for reindexing after major codebase changes, ensuring accurate semantic code search results.
Search enterprise codebases using semantic AI to find relevant code snippets across local projects and Git repositories based on natural language queries.
HTTP-based server that provides semantic code search capabilities to IDEs through the Model Context Protocol, allowing efficient codebase exploration without repeated indexing.
Enables semantic search and retrieval of code files using embeddings stored in PostgreSQL. Supports intelligent codebase exploration through natural language queries, file listing, and content retrieval.
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.