BAI-LAB/MemoryOS

Health v2 · maintenance only

Adoption not part of the score

1561 stars · 160 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MemoryOS is a Python library that provides an operating-system-inspired memory layer for personalized AI agents, using a hierarchical short/mid/long-term storage architecture with storage, updating, retrieval, and generation modules. It ships as a plug-and-play SDK plus an MCP server so any LLM-backed application can gain persistent long-term memory.

Use cases

• add long-term memory to my ai agent
• make chatbot remember user preferences across sessions
• store user profile and knowledge base for personalized llm responses
• plug memory into claude desktop or cursor via mcp
• improve multi-turn conversation coherence with llm
• keep chat history local without sending data to cloud
• benchmark agent memory on locomo

When to choose

• you need persistent, personalized memory for LLM agents with SOTA benchmark results
• you want an MCP server to inject memory into existing AI clients like Claude Desktop or Cursor
• you need pluggable storage, update, and retrieval strategies and local data storage for privacy

When to avoid

• you only need simple short-context conversation without cross-session memory
• you need a fully managed cloud memory service rather than a self-hosted Python library
• your stack is not Python or LLM-agnostic tooling is required

Facets

library · maturity active

rag agent-framework llm-inference mcp chatbot search-engine large-language-models developer-tools python cross-platform self-hosted long-term-memory memory-management personalization mcp-server hierarchical-storage emnlp-2025 ai-agents retrieval-augmented-generation natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="BAI-LAB/MemoryOS")