by RikyZ90 · MCP Server · ★ 84
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install shibaclaw
Taken from the project's README on GitHub. Check the security audit before running it.
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.
| Stars | 84 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 59/100 |
| Last Updated | 2026-10-20 |
| Created | 2026-03-20 |
| Platforms | browser, docker, mcp, python |
| Est. Tokens | ~19k |
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
Looking for a ShibaClaw alternative? If you're comparing ShibaClaw with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Self-hosted framework for orchestrating fleets of specialist AI agents — ensemble reasoning and a full agentic
c4 GenAI Suite
Your Digital Companion. Self-hosted Telegram bot orchestrating multiple AI providers (OpenAI, Anthropic, Googl
Polymcp provides a simple and efficient way to interact with MCP servers using custom agents
Turn feature specs into merged PRs with a self-supervising swarm of coding agents — parallel execution, isolat
Explore other popular mcp server tools:
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: