Embedding Search

This MCP server implementation, developed by Scott Spence, provides embedding search capabilities for transcripts. It utilizes a SQLite database to store and query embeddings, allowing for efficient semantic search across large volumes of text data. The implementation is designed for use cases requiring quick retrieval of relevant transcript segments based on semantic similarity, such as in podcast analysis, speech-to-text applications, or content recommendation systems.