by vincentkoc · MCP Server · ★ 144
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Flagged: reads agent memory. 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 | 144 |
| Forks | 79 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 55/100 |
| Open Issues | 64 |
| Last Updated | 2026-04-20 |
| Created | 2026-02-09 |
| Platforms | mcp |
| Est. Tokens | ~46k |
Awesome OpenClaw English Русский A curated list of high-signal resources for OpenClaw (formerly Moltbot, originally Clawdbot): frameworks, skills, tooling, deployments, and real-world use cases. OpenClaw is an open-source, self-hosted AI agent framework that connects LLMs to tools, messaging channels, and memory systems so agents can execute real workflows.
Looking for a awesome-openclaw alternative? If you're comparing awesome-openclaw 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.
A collection of AI agent skills for Clawdbot, Claude Code, Codex
OpenClaw Skills 中文精选:2,868 个社区 Skills 分类整理 + 国产模型接入指南(DeepSeek/Qwen/GLM/Moonshot)|Awesome OpenClaw skills in C
The brutally honest map of where AI-agent money actually flows. Every number measured, dated, and re-checked —
The definitive resource for Agent Skills - modular capabilities revolutionizing AI agent architecture
OpenClaw-inspired autonomous AI agent built entirely in n8n. Adaptive RAG-powered memory, Skills via MCP templ
MCP server for SSH: let Claude Code, Codex and any MCP client run commands, transfer files and manage servers
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: