Indexes and performs semantic searches across files in local directories using vector embeddings.
Sponsored
Enables semantic search across a local file system by watching specified directories, creating vector embeddings of file contents, and providing search and statistics functionalities. It integrates with Model Context Protocol (MCP) and supports configurable chunking, file ignoring, and real-time updates for file changes and deletions.
Key Features
01Real-time file watching and indexing
02Background processing of files
03Semantic search using vector embeddings
04Automatic handling of file changes and deletions
05Configurable chunk size and overlap
0616 GitHub stars
Use Cases
01Searching code repositories for relevant code snippets
02Finding specific information within a large collection of documents
03Creating a knowledge base with semantic search capabilities
