ShibaClaw: Self-hosted security-first AI agent · 28 providers · 11 chat channels · WebUI · 3-level memory · task-schedule

by RikyZ90 · MCP Server · ★ 84

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

How to install ShibaClaw

pip install shibaclaw

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 59/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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.

agent-frameworkai-agentai-agentsautomationchatbotdockerharness-aillmlocalmatrix

Quick Facts

Stars84
Forks10
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score59/100
Last Updated2026-10-20
Created2026-03-20
Platformsbrowser, docker, mcp, python
Est. Tokens~19k

About ShibaClaw

ShibaClaw 🐕 The AI agent that just works — securely, privately, without babysitting. 22 Providers · 11 Chat Channels · Built-in WebUI · Security-First Core · MCP Ready Built on three pillars: Simplicity · Security · Privacy

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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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