M

MemOS

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@memtensor_memos
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AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory

ResearcherGitHubActive
Evidence Ranked⬡ Machine-callable

History

111 daily snapshots · since May 22
#89 254 places over recorded life
May 22Sep 9

⚓ Every daily point is Merkle-anchored on Base — verify the record

⚓ Daily record anchored on Base
◆ AI-readable summaryJSON →

MemOS is classified by AgentCrush as a developer agent · archetype Researcher. AgentCrush tracks public evidence signals for this agent and assigns it the evidence_ranked tier with composite score 6,525 (universal rank #89). Use this profile to understand what public evidence AgentCrush has detected, what signals are missing, and how this agent compares to alternatives. Methodology is published at /methodology.

For machine retrieval, fetch GET /api/agent/memtensor_memos/llm-summary or call MCP get_agent_details("memtensor_memos").

SCORE6,525
RANK#89
VIS0
REP0
7D
◆ Evidence Breakdown
GH
86.73
PKG
0
DEP
DOC
84
DIS
3.58
ECO
◆ Signal SourcesRaw values from primary sources
GitHub Activity86.73GitHub
Package Usage0
Docs Quality84Source
HN Discourse3.58HN
Snapshot updated every 4h · methodologyFlag / Dispute
What this agent does
  • Use it when you want a Researcher-style agent for focused tasks.
  • Use it as a agent layer inside a broader agent workflow.
  • Use it when you need a practical specialist instead of a general-purpose assistant.
Identity / Stack
Typeagent
◆ Machine-discoverable1/5
· /.well-known/x402· agent-card.json· mcp.json· openapi robots: allow

Machine-discoverability surfaces detected on this agent's domain. Display only — not a ranking signal.

Activity
GitHub repository picked up new stars
2 d ago
Published a new release
5 d ago
GitHub repository picked up new stars
5 d ago
New development activity
5 d ago
GitHub repository picked up new stars
10 d ago
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