simplemem

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Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval

modbender By modbender schedule Updated 3/6/2026

name: simplemem

version: 1.0.0

description: Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval

metadata: {"openclaw": {"emoji": "🧠", "requires": {"bins": ["python"], "env": ["OPENAI_API_KEY"]}, "primaryEnv": "OPENAI_API_KEY", "homepage": "https://github.com/aiming-lab/SimpleMem"}}


SimpleMem Skill

Integrates SimpleMem: Efficient Lifelong Memory for LLM Agents into OpenClaw.

What it does

SimpleMem provides semantic memory compression and retrieval for agents:

  • Store: Compresses interactions into compact memory units

  • Synthesize: Merges related memories on-the-fly

  • Retrieve: Intent-aware planning for efficient context retrieval

Installation


# Install Python dependency

pip install simplemem



# Or via repo

git clone https://github.com/aiming-lab/SimpleMem.git

cd SimpleMem

pip install -r requirements.txt

Configuration (Optional - Full Features)

For full SimpleMem features, set your OpenAI API key:


$env:OPENAI_API_KEY = "your-openai-key"

Without API key: Uses JSON fallback (basic keyword search)

With API key: Uses full SimpleMem with semantic embeddings

Usage

PowerShell Script


# Agregar memoria

.\simplemem.ps1 -Action add -Content "El usuario prefiere cafe con leche de avena"



# Buscar memorias

.\simplemem.ps1 -Action search -Query "cafe"



# Ver estadisticas

.\simplemem.ps1 -Action stats

Python API


from simplemem import SimpleMemSystem, set_config, SimpleMemConfig



# With API key (full features)

config = SimpleMemConfig()

config.openai_api_key = "your-key"

set_config(config)

system = SimpleMemSystem()



# Add memory

system.add("User preference: coffee with oat milk", user_id="user1")



# Retrieve

results = system.retrieve("What does user like?", user_id="user1")

Key Features

  • Cross-session memory: Persistent across conversations (64% better than Claude-Mem)

  • Semantic compression: 43.24% F1 on LoCoMo benchmark

  • Fast retrieval: 388ms average retrieval time

  • Multi-index: Semantic + Lexical + Symbolic layers

  • Fallback: JSON-based storage when no API key available

Files

  • simplemem.py - Main Python wrapper

  • simplemem.ps1 - PowerShell CLI script

  • data/ - Storage directory (created on first use)

Credits

Install via CLI
npx skills add https://github.com/modbender/skill-library-mcp --skill simplemem
Repository Details
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