Memori and Memary

These are direct competitors offering similar SQL-based memory persistence layers for LLM agents, with MemoriLabs' implementation achieving significantly broader adoption and maintenance based on download and star metrics.

Memori
75
Verified
Memary
54
Established
Maintenance 20/25
Adoption 11/25
Maturity 24/25
Community 20/25
Maintenance 0/25
Adoption 10/25
Maturity 25/25
Community 19/25
Stars: 12,351
Forks: 1,112
Downloads:
Commits (30d): 45
Language: Python
License:
Stars: 2,576
Forks: 193
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No risk flags
Stale 6m

About Memori

MemoriLabs/Memori

SQL Native Memory Layer for LLMs, AI Agents & Multi-Agent Systems

This tool helps developers give their AI agents and large language models (LLMs) the ability to remember past interactions and learn from what they do, not just what they say. It takes conversations and actions from your agents and uses them to provide relevant context for future interactions. This is for developers building AI agents, multi-agent systems, or applications that use LLMs, who want their AI to have persistent, long-term memory.

AI-agent-development LLM-application-development conversational-AI memory-management AI-workflow-enhancement

About Memary

kingjulio8238/Memary

The Open Source Memory Layer For Autonomous Agents

Memary helps developers create AI agents that can remember and learn over time, much like humans do. It takes in user and system personas, along with past interactions and knowledge stores, to produce agents capable of more complex and continuous reasoning. This tool is designed for AI developers and researchers building autonomous agents or conversational AI systems.

AI-agent-development conversational-AI large-language-models AI-research autonomous-systems

Scores updated daily from GitHub, PyPI, and npm data. How scores work