Flagged: installs a cron job. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by melgarafael · MCP Server · ★ 3.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is DeskcommCRM safe to install? View the security audit →
🛠️ DeskcommCRM CRM operacional multi-tenant para e-commerce, com IA conversacional nativa, WhatsApp via WAHA e LGPD by-design. 📘 Setup Guide · 🏗️ Arquitetura · 🤝 Contribuir · 📋 PRDs · 🗺️ Roadmap ### ☁️ Rode este CRM em produção com 1 comando O DeskcommCRM foi desenvolvido em parceria com a HostGator: o instala o CRM completo (app + WAHA + banco) numa VPS com um único comando, e o runbook de produção já assume esse ambiente. 👉 Assinar a VPS HostGator com desconto da parceria — datacenter em São Paulo, ideal pro WhatsApp rodando 24/7. (link de parceiro — assinar por ele apoia o projeto e sai mais barato) ✨ O que é DeskcommCRM unifica atendimento h
| Stars | 3,347 |
| Forks | 813 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 63.9597746404972/100 |
| Open Issues | 115 |
| Last Updated | 2026-09-20 |
| Created | 2026-04-28 |
| Platforms | mcp, node |
| Est. Tokens | ~17k |
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DeskcommCRM is Open-source AI sales OS — self-hosted CRM with native AI agents + WhatsApp (WAHA). Open alternative to Kommo, Octadesk & Intercom for any business that sells by chat. MCP-ready, multi-tenant, LGPD.. It is categorized as a MCP Server with 3.3k GitHub stars.
DeskcommCRM is primarily written in TypeScript. It covers topics such as ai, ai-agents, chatbot.
You can find installation instructions and usage details in the DeskcommCRM GitHub repository at github.com/melgarafael/DeskcommCRM. The project has 3.3k stars and 813 forks, indicating an active community.
DeskcommCRM is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to DeskcommCRM on Agent Skills Hub include voltagent, webiny-js, relaticle. 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: