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
Indexed · Awaiting Evidence⬡ Machine-callable

History

66 daily snapshots · since May 22
#194 149 places over recorded life
May 22Jul 26

⚓ 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 indexed tier with composite score 5,008 (universal rank #194). 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").

SCORE5,008
RANK#194
VIS0
REP0
7D
◌ Evidence Progress
GH
0
PKG
DEP
DOC
DIS
0
ECO
◆ Signal SourcesRaw values from primary sources
GitHub Activity86.16GitHub
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
31 min ago
GitHub repository picked up new stars
8 h ago
GitHub repository picked up new stars
12 h ago
New development activity
12 h ago
GitHub repository picked up new stars
1 d ago
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