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 sbhooley · MCP Server · ★ 671
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ainativelang safe to install? View the security audit →
AI Native Lang (AINL) Find Us on X: @ainativelang <a h
| Stars | 671 |
| Forks | 24 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 62.4351708916008/100 |
| Open Issues | 12 |
| Last Updated | 2026-09-03 |
| Created | 2026-03-10 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~25k |
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ainativelang is AINL helps turn AI from "a smart conversation" into "a structured worker." It is designed for teams building AI workflows that need multiple steps, state and memory, tool use, repeatable execution, v. It is categorized as a MCP Server with 671 GitHub stars.
ainativelang is primarily written in Python. It covers topics such as agent-orchestration, ai-agents, ai-native-language.
You can find installation instructions and usage details in the ainativelang GitHub repository at github.com/sbhooley/ainativelang. The project has 671 stars and 24 forks, indicating an active community.
ainativelang is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to ainativelang on Agent Skills Hub include bernstein, captain-claw, MeiGen-AI-Design-MCP. 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: