SimpleMem

SimpleMem is an open-source memory package that stores, compresses, and retrieves long-term memories for LLM agents.

SimpleMem is a unified memory stack and Python package designed for LLM agents. It stores, compresses, and retrieves long-term memories across text, image, audio, and video modalities. The system processes dialogues or raw data into structured memory units and uses intent-aware retrieval planning to fetch relevant information. It supports text memory via MCP and multimodal memory through Python integration. Additionally, it includes an optimization feature to tune retrieval configurations for specific datasets.

SimpleMem at a glance

Best for: Software engineer, Researcher
Runs on: Python, API, MCP Client, Claude Desktop, Cursor, LM Studio, Cherry Studio, PyPI Package, open source
Pricing: Free
Released: January 2026
Category: AI agent tool
Website: github.com/aiming-lab/SimpleMem

Key features

Store and compress long-term memories
Support text, image, audio, and video inputs
Automatic backend routing for text or multimodal modes
Intent-aware retrieval planning
Self-evolving retrieval configuration optimization
Parallel processing for large-scale dialogue datasets
Integration with MCP clients and Python environments

Use it for

Maintaining long-term context in LLM agent dialogues
Processing multimodal memory including images, audio, and video
Optimizing retrieval configurations for custom dev sets
Running batch operations with parallel processing

Alternatives to SimpleMem

Supermemory — Integrates long-term memory into AI coding agents with a single prompt.
memU — It gives every connected agent a shared and inspectable memory layer.
ReMe — It enables local-first, file-native long-term memory sharing across multiple AI agents.
Adaptive Agent Memory Research — It decides what to remember based on measured future utility rather than query similarity.
Memvid — Single-file architecture replaces complex RAG pipelines with portable storage.
Memori — Reduces LLM token usage and spend by over 97% with targeted recall.
Agentmemoryrepo — Enables agents to navigate memories like a wiki and share knowledge across sessions.
Mem0 — It provides drop-in persistent memory for AI agents without changing pipelines.
MemMachine — Provides long-term persistent memory for LLM-based agents.
LongMemory — Provides immutable, temporal, and governed recall instead of simple vector retrieval.
MuscleMemory — It cuts input tokens, tool calls, and execution time while maintaining task success.
AgentMemory — It runs locally with zero external databases and achieves high retrieval recall.

All SimpleMem alternatives