inAI-wiki — security grade SAFE, quality 55/100

Security audit verdict: SAFE · quality 55/100

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 inai-sandy · MCP Server · ★ 53

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

🔒 Is inAI-wiki safe to install? View the security audit →

About inAI-wiki

🚀 INAI • The Open AI Hub ⭐ If you like this project, please star it on GitHub — it helps a lot! ⭐ Maintained by Sandeep Karnati • Latest updates 👉 inai.wiki 📖 See CONTRIBUTING.md for step-by-step instructions. 🌍 INAI • The Open AI Hub <

agentsaiaitoolsartificial-intelligencechrome-extensionsdatabasedatasetllmllmsmachine-learning

Quick Facts

Stars53
Forks10
CategoryMCP Server
Quality Score54.5308580135315/100
Open Issues7
Last Updated2026-04-16
Created2025-06-22
Platformsbrowser, mcp
Est. Tokens~839k

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Frequently Asked Questions

What is inAI-wiki?

inAI-wiki is 🌍 The open-source Wikipedia of AI — 2M+ apps, agents, LLMs & datasets. Updated daily with tools, tutorials & news.. It is categorized as a MCP Server with 53 GitHub stars.

How do I install or use inAI-wiki?

You can find installation instructions and usage details in the inAI-wiki GitHub repository at github.com/inai-sandy/inAI-wiki. The project has 53 stars and 10 forks, indicating an active community.

What are the best alternatives to inAI-wiki?

The top alternatives to inAI-wiki on Agent Skills Hub include mcp-server-atlassian-jira, boilerplate-mcp-server, penpot-mcp. 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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