Store content in a vector database for semantic search and retrieval using embeddings. Save text with unique identifiers to enable similarity-based queries.
Store content in a vector database for semantic search and retrieval using natural language queries. Save text with unique identifiers to enable similarity-based information lookup.
An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.
Enables recording, querying, and summarizing daily work entries with tags using a local SQLite database. Supports work logging, search, timeline queries, tag management, and automated reminders for tracking daily tasks.
A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.