Provides a persistent, semantic memory system for large language models to overcome context limitations across conversations.
MnemoX Lite is an experimental Model Context Protocol (MCP) server designed to address a fundamental limitation of Large Language Models: their inability to retain context across separate conversations. It implements a sophisticated semantic memory system that intelligently chunks, contextualizes, and stores information using vector embeddings. This allows LLMs to recall relevant insights, project decisions, and accumulated knowledge through natural language queries, operating transparently in the background to ensure persistent, curated memory.