SimpleMem and memsearch

SimpleMem provides a general-purpose lifelong memory framework for LLM agents with vector storage and retrieval optimization, while MemSearch offers a Markdown-first memory interface layer that could complement SimpleMem by providing structured memory formatting and search capabilities on top of it.

SimpleMem
81
Verified
memsearch
62
Established
Maintenance 20/25
Adoption 19/25
Maturity 22/25
Community 20/25
Maintenance 25/25
Adoption 10/25
Maturity 9/25
Community 18/25
Stars: 3,182
Forks: 310
Downloads: 2,317
Commits (30d): 11
Language: Python
License: MIT
Stars: 846
Forks: 77
Downloads:
Commits (30d): 110
Language: Python
License: MIT
No risk flags
No Package No Dependents

About SimpleMem

aiming-lab/SimpleMem

SimpleMem: Efficient Lifelong Memory for LLM Agents

Implements a three-stage semantic compression pipeline—structured compression, online synthesis, and intent-aware retrieval—to maximize information density while minimizing token overhead. Exposes memory functionality through MCP (Model Context Protocol) servers and Python packages, integrating with Claude Desktop, Cursor, LM Studio, and other AI platforms. Supports persistent cross-session memory that reportedly outperforms Claude's native memory by 64% on standard benchmarks.

About memsearch

zilliztech/memsearch

A Markdown-first memory system, a standalone library for any AI agent. Inspired by OpenClaw.

Implements semantic search over markdown files using pluggable embedding providers (ONNX, Google, Voyage, Ollama, local), with automatic file watching and SHA-256 dedup to skip re-embedding unchanged content. Stores vectors in a local database and exposes a simple async Python API that integrates seamlessly with LLM frameworks like OpenAI, Anthropic Claude, and Ollama for agent-driven recall-think-remember loops.

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