by rohitg00 · MCP Server · ★ 69.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-engineering-from-scratch safe to install? View the security audit →
Journey • Get Started • Toolkit • Roadmap • Contribute • Glossary 230+ hands-on lessons across 20 phases. From linear algebra to autonomous agent swarms. Python, TypeScript, Rust, Julia. Every lesson produces something reusable: prompts, skills, agents, MCP servers. You learn AI. You build real things. You ship tools others can use. "I learned some
git clone https://github.com/rohitg00/ai-engineering-from-scratch.gitTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 69,085 |
| Forks | 12,104 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 60.5978026395501/100 |
| Open Issues | 80 |
| Last Updated | 2026-10-14 |
| Created | 2026-03-18 |
| Platforms | mcp, python |
| Est. Tokens | ~19k |
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ai-engineering-from-scratch is Learn AI Engineering! Learn it. Build it. Ship it for others.. It is categorized as a MCP Server with 69.1k GitHub stars.
ai-engineering-from-scratch is primarily written in Python. It covers topics such as agents, ai, ai-agents.
The README on GitHub (github.com/rohitg00/ai-engineering-from-scratch) gives: git clone https://github.com/rohitg00/ai-engineering-from-scratch.git. Usage details are in the same README.
ai-engineering-from-scratch is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-engineering-from-scratch on Agent Skills Hub include langchain, repomix, ai-guide. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: