MCPFast / Tools / Memory Cloud: Adaptive memory for AI agents & teams
Self-hosted MCP server with hybrid search and a neural memory graph that learns to enhance AI agents beyond RAG.
View on GitHub→Memory Cloud is a self-hosted MCP server designed to provide advanced, adaptive memory capabilities for AI agents and teams. It goes beyond traditional Retrieval Augmented Generation (RAG) by implementing a hybrid search system and a dynamic neural memory graph. This allows AI agents to learn and evolve their memory, leading to more sophisticated and context-aware interactions and task execution.
Memory Cloud acts as a central memory repository for AI agents. It stores and retrieves information using a combination of keyword-based and semantic search methods (hybrid search). Crucially, it builds a neural memory graph that represents the relationships and connections between pieces of information. This graph is not static; it learns and adapts over time as the AI interacts with data and performs tasks. This adaptive learning enables agents to recall information more effectively, understand complex contexts, and make better decisions.
Memory Cloud is specifically built for AI developers and teams working on complex AI agent systems. This includes: