Memoh: Self hosted, always-on AI agent platform run in containers

by memohai · Codex Skill · ★ 2.0k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 67/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars2,045
Forks196
LanguageGo
CategoryCodex Skill
LicenseAGPL-3.0
Quality Score67/100
Open Issues43
Last Updated2026-08-07
Created2026-01-12
Platformsgo
Est. Tokens~4556k

About Memoh

[English] [简体中文] Memoh Multi-Member, Structured Long-Memory, Containerized AI Agent System. 📌 Introduction to Memoh - The Case for an Always-On, Containerized Home Agent [Telegram Group] [Documentation] [Cooperation] Memoh is an always-on, co

Compatible Skills

These tools work well together with Memoh for enhanced workflows:

  • goclaw — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (59%)
  • clawlet — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • ChatClaw — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • awesome-openclaw — semantic(0.30)+complementary+rare_topics+similar_pop (50%)
  • Claude-to-IM-skill — semantic(0.32)+complementary+similar_pop (46%)

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    This is MCP server for Claude that gives it terminal control, file system search and diff file editing capabil

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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