by vortezwohl · MCP Server · ★ 213
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install -U autono
pip install git+https://github.com/vortezwohl/Autono.git
Taken from the project's README on GitHub.
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.
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 | 213 |
| Forks | 40 |
| Language | Python |
| Category | MCP Server |
| License | GPL-3.0 |
| Quality Score | 53/100 |
| Open Issues | 17 |
| Last Updated | 2026-06-23 |
| Created | 2024-10-25 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~16k |
A ReAct Based Highly Robust Autonomous Agent Framework. MCP is currently supported. How to use McpAgent. English | 繁體中文 | 简体中文</
Looking for a Autono alternative? If you're comparing Autono 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.
An autonomous HR agent that can answer user queries using tools
An introduction to the world of AI Agents
An agent runtime for Python. Give your agent real work. Keep control: every action checked before it runs, eve
Open-source protocol suite standardizing LLM, Vector, Graph, and Embedding infrastructure across LangChain, Ll
An md file as a chat interface and editable history in one.
Agent samples built using the Strands Agents SDK.
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: