by matiasbattocchia · MCP Server · ★ 266
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is wakit-api safe to install? View the security audit →
wakit API Open-source WhatsApp Business Platform Self-hostable, multi-tenant, AI-agent ready. Built with Deno 🦕 and Postgres 🐘, powered by Supabase ⚡ wakit is designed for both individual businesses and service providers. You can use it to manage your own WhatsApp messaging, or leverage its features to become a Meta Business Partner and offer WhatsApp messaging services to other organizations. 🚀 Powering production-grade AI agents at Mirlo.com [!NOTE] This p
/plugin marketplace add matiasbattocchia/wakit-api
/plugin install wakit@matiasbattocchia-wakit-apiTaken 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 | 266 |
| Forks | 83 |
| Language | TypeScript |
| Category | MCP Server |
| License | Unlicense |
| Quality Score | 66/100 |
| Open Issues | 5 |
| Last Updated | 2026-05-06 |
| Created | 2025-08-21 |
| Platforms | mcp, node |
| Est. Tokens | ~209k |
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wakit-api is Open-source WhatsApp Business platform. It is categorized as a MCP Server with 266 GitHub stars.
wakit-api is primarily written in TypeScript. It covers topics such as agents, ai, ai-agents.
The README on GitHub (github.com/matiasbattocchia/wakit-api) gives: /plugin marketplace add matiasbattocchia/wakit-api , then /plugin install wakit@matiasbattocchia-wakit-api. Usage details are in the same README.
wakit-api is released under the Unlicense license, making it free to use and modify according to the license terms.
The top alternatives to wakit-api on Agent Skills Hub include Nubase, n8n-claw, nerve. 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: