MemOS
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
70views this month
Decision brief
MemOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks.
Good fit when
- If you require ultra-persistent memory management within your application for long-term storage.
- For applications where token savings are significant benefits; MemOS can offer up to 35.24% in savings.
Avoid when
- If you prefer fully managed solutions and have no preference over where your data is stored (hosted in MemOS Cloud).
- When minimal setup overhead is a critical requirement since self-hosting MemOS necessitates Neo4j and Qdrant for optimal performance.
- Pricing:
- unknown - Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs.
- Requirements:
- Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components.
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Aug 18, 2026
- Provenance
- Not a fork · Organization account
- As of Aug 18, 2026
- Security (OSV)
- 2 low (2 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install MemOSHow it fits your stack(8)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
Alternative
Integrates
Relationship graph
Optional deeper exploration of typed edges and category neighbours.
Similar tools
Same-category neighbours not already linked as typed edges.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
MemOS is a self-evolving operating system designed for Long-Short Term Memory (LSTM) systems and AI agents. It supports ultra-persistent memory, hybrid retrieval technologies, and enables the reuse of skills across tasks to save tokens.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 18, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 18, 2026
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 18, 2026
- Languages
- typescript, python
Source: github.language+pyproject.toml · Aug 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 18, 2026)
| Get an API key | docker compose up | openclaw plugins install | npm install + agent-specific setup |Source link
Tags
README
🚀 Quick Start MemOS is built around four entry points. Pick the one that matches your scenario. Cloud API Self Host MemOS Cloud Plugin Local Plugin Best for Your app, fully managed Teams on own infra OpenClaw users, zero ops DeepSeek Harness, Hermes, or OpenClaw; on device Setup...
For agents
This page has a .md twin and JSON over the API.