Manages the storage and retrieval of conversational memories for multiple large language models.
Memory is a Model Context Protocol (MCP) server designed to persistently log and retrieve conversational memories from various Large Language Models (LLMs). It offers a robust solution for enhancing LLM capabilities by allowing them to store, retrieve, append, and clear user-specific conversation data. Utilizing MongoDB for storage, it ensures data persistence and provides a structured way to manage LLM interactions, enabling richer and more context-aware conversations.
Características Principales
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02Retrieve all stored memories
03Append new memories without overwriting
04Clear all stored memories
05Persistent storage using MongoDB
06Save and overwrite LLM memories
Casos de Uso
01Storing ongoing conversation context for an LLM to refer back to
02Allowing LLMs to retrieve historical interactions for personalized responses
03Enabling LLMs to add new data points to existing memory sets
