awesome-ai-startups: A curated list of indie-built AI startups — bootstrapped, pre-seed, and angel-funded products only

by nowork-studio · MCP Server · ★ 133

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

Security audit verdict: SAFE · quality 54/100

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.

ai-agentsai-toolsawesomeawesome-aiawesome-listgeomarketingmarketing-automationmarketing-toolsmcp

Quick Facts

Stars133
Forks92
CategoryMCP Server
LicenseCC0-1.0
Quality Score54/100
Open Issues66
Last Updated2026-10-09
Created2026-05-09
Platformsmcp
Est. Tokens~28k

About awesome-ai-startups

Awesome AI Startups A curated directory of AI startups built by independent founders — bootstrapped, pre-seed, and angel-funded products from outside the big AI labs. The goal: make useful indie AI products easier to find, share, and support. Building one? Add your startup by opening a PR — see contributing.md for the format and inclusion criteria.

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How this security grade is produced

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:

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