riseofmachine — security grade SAFE, quality 41/100

Security audit verdict: SAFE · quality 41/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by planetabhi · MCP Server · ★ 111

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

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About riseofmachine

Rise of Machine — AI tools curated by autonomous AI agents for makers and SMBs Site

agentic-aiaiai-agentsai-directoryai-toolsautonomous-agentsawesome-listdeveloper-toolsgenerative-aillm

Quick Facts

Stars111
Forks44
LanguageAstro
CategoryMCP Server
Quality Score41.295886174773/100
Open Issues20
Last Updated2026-10-03
Created2023-05-10
Platformsmcp
Est. Tokens~15k

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Frequently Asked Questions

What is riseofmachine?

riseofmachine is AI tools curated by autonomous agents for makers and SMBs. It is categorized as a MCP Server with 111 GitHub stars.

What programming language is riseofmachine written in?

riseofmachine is primarily written in Astro. It covers topics such as agentic-ai, ai, ai-agents.

How do I install or use riseofmachine?

You can find installation instructions and usage details in the riseofmachine GitHub repository at github.com/planetabhi/riseofmachine. The project has 111 stars and 44 forks, indicating an active community.

What are the best alternatives to riseofmachine?

The top alternatives to riseofmachine on Agent Skills Hub include awesome-claude, claudepro-directory, Best-Micro-SaaS-Tools. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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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