Memanto

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An open-source memory layer for AI agents featuring a 7-layer memory architecture that supports short-term, long-term, and semantic memory with RAG-based retrieval.

Author Moorcheh AI Open Sourced 2026-03-23 Last Commit Unknown

Overview

Memanto is an open-source memory layer for AI agents featuring a 7-layer memory architecture that supports short-term, long-term, and semantic memory. It integrates with popular frameworks including CrewAI and LangChain, and provides RAG-based retrieval for context-aware agent interactions.

Key Features

7-layer memory architecture for AI agents
Long-term and semantic memory support
Integration with CrewAI and LangChain
RAG-based context retrieval

Use Cases

Adding persistent memory to stateless LLM-based agents
Building context-aware conversational AI systems
Enabling long-term knowledge retention for autonomous agents

Technical Details

7-layer memory architecture covering short-term, working, episodic, semantic, procedural, long-term, and meta memory
Supports RAG-based retrieval for efficient context lookups
Compatible with CrewAI, LangChain, and standalone usage