head to head · open source
pentagi vs ARL-Next
pentagi has 33,619 GitHub stars, 5,256 forks, 71 open issues and last shipped 17 days ago. ARL-Next has 504 stars, 92 forks, 5 open issues and last shipped 3 days ago. pentagi leads on adoption by 6,570% (33,619 vs 504 stars). pentagi is written in Go under MIT; ARL-Next is written in Python under GPL-3.0. pentagi has attracted 16% as many forks as stars, ARL-Next 18%. ARL-Next was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| pentagi | ARL-Next | |
|---|---|---|
| GitHub stars | ★ 34K | ★ 504 |
| License | MIT | GPL-3.0 |
| Written in | Go | Python |
| Last push | 2026-10-22 | 2026-11-05 |
| Forks | ⑂ 5.3K | ⑂ 92 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick pentagi if
- You weight community size — 34K stars and counting
- You want the MIT license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick ARL-Next if
- You want the ARL-Next feature set and don't need the biggest community
- You prefer the GPL-3.0 license terms
- Your stack matches Python
- You evaluated both and ARL-Next fits your workflow better
About pentagi
PentAGI P enetration testing A rtificial G eneral I ntelligence Join the Community! Connect with security researchers, AI enthusiasts, and fellow ethical hackers. Get support, share insights, and stay updated with the latest PentAGI developments. ⠀ Table of Contents Overview Features Architecture Agent Supervision Quick Start Agent Docker Access Running Several Instances How to Use PentAGI After Login API Access LLM Provider Configuration Ollama OpenAI Anthropic Google AI (Gemini) AWS Bedrock DeepSeek GLM Kimi Qwen MiniMax Advanced Setup Langfuse Integration Monitoring and Observability Knowledge Graph…
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About ARL-Next
English 简体中文 ARL Next 现代化资产测绘与漏洞监控平台 Modern Attack Surface Reconnaissance & Asset Intelligence Platform 企业资产关联 · 异步解耦调度 · 原生 MCP 协议集成 · 容器化开箱部署 🚀 快速入门（5 分钟） • ⚡ 快速部署指南 • 💡 架构演进对比 • ✨ 核心特性 • 🔌 API对接指南 • 🤖 MCP配置指南 • 🎯 MCP实战用例 • 📜 更新日志 • 💬 讨论交流 • 📄 开源协议 💡 什么是 ARL Next？ ARL Next 是基于经典开源项目 ARL (资产侦察灯塔) 进行架构重构与持续演进的资产测绘平台。 针对大规模扫描场景下的任务队列阻塞、长时间运行内存增长以及历史依赖过时等工程瓶颈，系统实施了微服务拆分与异步任务解耦，全面升级现代运行时环境与测绘工具链，并集成了 Model Context Protocol (MCP) 标准协议，支持自动化资产透视与 AI 协同分析。 💡 架构演进与技术方案基准对比 ✨ 核心特性矩阵 🤖 AI Agent 原生集成与 MCP 治理中心 (MCP 2.0) ：遵循 Model Context Protocol (2024 11 05) 标准，提供 远程原生 SSE 直连 （Cursor / Claude Desktop 粘贴即用）与 本地…
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Frequently asked questions
Is pentagi or ARL-Next more popular?
pentagi has 33,619 GitHub stars and ARL-Next has 504. pentagi has the larger community by that measure.
Are pentagi and ARL-Next free?
Both are open source. pentagi is licensed under MIT and ARL-Next under GPL-3.0. Neither carries a licence fee.
What is the difference between pentagi and ARL-Next?
pentagi is written in Go and ARL-Next in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, pentagi or ARL-Next?
Choose pentagi if you want the larger community (33,619 stars) or its MIT licence terms. Choose ARL-Next if its feature set, stack or GPL-3.0 licence fits better. Both are self-hostable.