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MemOS (MemTensor)
Memory OS for LLMs and agents: unified add/retrieve/edit/delete API over a graph-structured memory, offered as cloud API, self-hosted service (Neo4j + Qdrant) and local plugins for OpenClaw, Hermes and DeepSeek Harness.
memos.openmem.net/Active
v2.0.34 released 2026-09-23; repo pushed 2026-10-24. (checked 2026-10-25)
In Agent memory
Where it stands apart
- Which shared standard or format does it mainly build on? a property-graph database (Neo4j, FalkorDB, Kuzu) (14% of 21 others)
What it shares with most of the community
- Is it actively maintained? active (67% of 21 others)
- How is the main thing licensed? permissive open source (MIT/Apache/BSD) (67% of 21 others)
- How is it mainly sustained? company with a paid product, tier, or ads (75% of 20 others)
- Can it run entirely on your own device or infrastructure, without the maker's servers? yes (67% of 21 others)
- Who is it for? developers (76% of 21 others)
- In the default setup, who mainly decides what gets remembered? the system, by extracting memories from conversations or data in the background (67% of 21 others)
- By default, how do old or wrong memories mainly go away? the system updates, merges, or decays them automatically (58% of 19 others)
- Does it work with models from different LLM vendors? yes, model-agnostic (86% of 21 others)
- Is there a first-party MCP server for it? yes (67% of 21 others)
- How is memory separated between users or tenants? built-in scoping by user, agent, session, or tenant IDs (62% of 21 others)
- Does it publish scores on public memory benchmarks (LoCoMo, LongMemEval, BEAM, etc.)? yes (62% of 21 others)
Nearest neighbors
- Cognee 76% of 17 shared answers match
- Honcho 76% of 17 shared answers match
- Supermemory 76% of 17 shared answers match
Every answer
| Question | Answer | Source |
|---|---|---|
| Is it actively maintained? | active | source 2026-10-25 |
| How is the main thing licensed? | permissive open source (MIT/Apache/BSD) Apache-2.0 | source 2026-10-25 |
| How is it mainly sustained? | company with a paid product, tier, or ads MemOS Cloud. | source 2026-10-25 |
| Can it run entirely on your own device or infrastructure, without the maker's servers? | yes | source 2026-10-25 |
| Do you need an account to use it? | optional account Self-host and local plugin need no MemOS account; Cloud API needs an mpg- key. | source 2026-10-26 |
| Who is it for? | developers | source 2026-10-25 |
| Which shared standard or format does it mainly build on? | stands apart a property-graph database (Neo4j, FalkorDB, Kuzu) Self-hosted on Neo4j plus Qdrant; cloud API leads. | source 2026-10-26 |
| In the default setup, who mainly decides what gets remembered? | the system, by extracting memories from conversations or data in the background Plugins auto-recall before tasks and retain experience after turns. | source 2026-10-25 |
| How can the person the memories are about see and edit them? | directly, as readable files or in a UI they control 'inspectable and editable by design'; local plugin ships a Memory Viewer dashboard. | source 2026-10-25 |
| By default, how do old or wrong memories mainly go away? | the system updates, merges, or decays them automatically Smart dedup, scheduler-driven lifecycle and skill evolution. | source 2026-10-25 |
| Where do memories live in the default setup the docs lead with? | in the vendor's cloud README leads with the Cloud API; self-host and local plugin also offered. | source 2026-10-25 |
| Does it work with models from different LLM vendors? | yes, model-agnostic | source 2026-10-25 |
| What is the main storage model for long-term memory? | knowledge graph (usually with vectors alongside) | source 2026-10-25 |
| What shape does it mainly take (the one its docs lead with)? | memory service (self-hosted server or hosted API) | source 2026-10-25 |
| Is there a first-party MCP server for it? | yes docs/en/open_source/modules/mos/memos_mcp.md | source 2026-10-25 |
| How is memory separated between users or tenants? | built-in scoping by user, agent, session, or tenant IDs Users and memory cubes. | source 2026-10-25 |
| Does it publish scores on public memory benchmarks (LoCoMo, LongMemEval, BEAM, etc.)? | yes LoCoMo 88.83, LongMemEval 89.20. | source 2026-10-25 |
Sources
This page was derived from:
- GitHub · github.com/MemTensor/MemOS · read 2026-10-25
- GitHub · github.com/MemTensor/MemOS/tree/main/docs/en/open_source/modules/mos · read 2026-10-25
- Web page · memos.openmem.net/ · read 2026-10-25
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