by Hainrixz · Agent Tool · ★ 426
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is whatsapp-agentkit safe to install? View the security audit →
Ver el sitio · Inicio rápido · Cómo funciona · FAQ About WhatsApp AgentKit convierte una conversación de 20 minutos en un agente de WhatsApp que atiende a tus clientes. No es una plantilla que copias y adaptas. Es un sistema de instrucciones que Claude Code lee para entrevistarte sobre tu negocio y después escribir, probar y desplegar el agente completo por ti: el servidor, la conexión con WhatsApp, la memoria de cada cliente y el prompt que le da personalidad. Tú no escribes código
git clone https://github.com/Hainrixz/whatsapp-agentkit.gitTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
| Stars | 426 |
| Forks | 135 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 61/100 |
| Open Issues | 10 |
| Last Updated | 2026-08-19 |
| Created | 2026-03-18 |
| Platforms | claude-code, python |
| Est. Tokens | ~13k |
These tools work well together with whatsapp-agentkit for enhanced workflows:
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whatsapp-agentkit is Construye tu agente de WhatsApp con IA en menos de 30 minutos. Claude Code te entrevista y escribe todo el código. Zernio o Meta Cloud API. Sin saber programar.. It is categorized as a Agent Tool with 426 GitHub stars.
whatsapp-agentkit is primarily written in Python. It covers topics such as ai-agent, anthropic, chatbot.
The README on GitHub (github.com/Hainrixz/whatsapp-agentkit) gives: git clone https://github.com/Hainrixz/whatsapp-agentkit.git. Usage details are in the same README.
whatsapp-agentkit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to whatsapp-agentkit on Agent Skills Hub include whatsapp-claude-plugin, ccproxy-api, claudex. 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: