head to head · open source
Agent-Reach vs VulnClaw
Agent-Reach has 108,014 GitHub stars, 9,640 forks, 137 open issues and last shipped 2 days ago. VulnClaw has 3,853 stars, 536 forks, 13 open issues and last shipped 4 days ago. Agent-Reach leads on adoption by 2,703% (108,014 vs 3,853 stars). Agent-Reach is written in Python under MIT; VulnClaw is written in Python under MIT. Agent-Reach has attracted 9% as many forks as stars, VulnClaw 14%. Agent-Reach was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-agent), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
← all 20902 open source comparisons
Side by side
| Agent-Reach | VulnClaw | |
|---|---|---|
| GitHub stars | ★ 108K | ★ 3.9K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-11-01 | 2026-10-30 |
| Forks | ⑂ 9.6K | ⑂ 536 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Agent-Reach if
- You weight community size — 108K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick VulnClaw if
- You want the VulnClaw feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and VulnClaw fits your workflow better
About Agent-Reach
👁️ Agent Reach 给你的 AI Agent 一键装上互联网能力 当下最稳的接入方式，替你选好、装好、体检好——接入方式会换代，你不用操心 快速开始 · English · 日本語 · 한국어 · 支持平台 · 设计理念 ❤️赞助商 想出现在这里？ 点击折叠 BrowserAct 支持从 Amazon、LinkedIn、X、Google Maps 等复杂网站提取你需要的任意数据。你只需用自然语言描述抓取需求，Agent 就会基于真实浏览器自动探索并测试页面流程，生成可靠、可复用的数据采集 Bot，并返回结构化结果。无需手动构建爬虫，无需编写代码。BrowserAct 内置隐身浏览、验证码处理和高质量住宅代理，帮助你更稳定地完成复杂网页数据采集。新用户注册即送 1000 积分， 立即免费试用 。 在腾讯云 Lighthouse 秒级部署 OpenClaw 全能助手，可通过对话丝滑接入 Agent Reach，给你的 OpenClaw 一键装上互联网能力。 CoreClaw 网页抓取平台与现成数据采集工具，CoreClaw 提供 100+ 现成数据采集工具，支持 Amazon、TikTok、Google Maps、Instagram、Facebook、YouTube 等平台，无需代码，支持 JSON/CSV 导出，仅对成功结果计费。 免费$3测试！ 优刻得星图astraflow大模型…
read the full Agent-Reach overview →
About VulnClaw
VulnClaw 🦞 AI 驱动的渗透测试 CLI 工具 — 说人话，打漏洞。 🌐 English version : README EN.md 本项目是可独立运行的 AI 渗透测试 Agent。 项目官网： 基于 LLM Agent + MCP 工具链 + 可选 Skill 参考资料， 配合 OpenAI / Anthropic / MiniMax / DeepSeek 等兼容模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。 快速开始 · 架构 · 内置 Skill 它能做什么 输入自然语言，AI 自动执行渗透测试全流程： 适用于已授权的渗透测试、CTF 竞赛、安全教学、红队演练等场景。 特性 模型主导求解引擎（默认） — 类似 Claude Code/Codex 的自主循环，模型自己决定下一步、何时调用工具、何时完成/询问/判定无路可走 AgentState 证据记忆 — 工具结果统一写入 AgentState.evidence ，raw 原文完整保留；active context 默认只注入高信号预览， evidence search / evidence view 用于按需回查原始证据 轻量纠偏层 — 工具调用前后记录重复调用、失败降级、耗时和新发现等信号；重复读取同一 evidence 范围会被抑制，连续证据空转会触发 stall…
read the full VulnClaw overview →
More in AI & Machine Learning
Related comparisons
More AI Development Platforms projects
Compare either of these against the rest of the AI Development Platforms field.
Frequently asked questions
Is Agent-Reach or VulnClaw more popular?
Agent-Reach has 108,014 GitHub stars and VulnClaw has 3,853. Agent-Reach has the larger community by that measure.
Are Agent-Reach and VulnClaw free?
Both are open source. Agent-Reach is licensed under MIT and VulnClaw under MIT. Neither carries a licence fee.
What is the difference between Agent-Reach and VulnClaw?
Agent-Reach is written in Python and VulnClaw 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, Agent-Reach or VulnClaw?
Choose Agent-Reach if you want the larger community (108,014 stars) or its MIT licence terms. Choose VulnClaw if its feature set, stack or MIT licence fits better. Both are self-hostable.