head to head · open source

Agent-Reach vs chonkie

Agent-Reach has 108,014 GitHub stars, 9,640 forks, 137 open issues and last shipped 2 days ago. chonkie has 4,818 stars, 368 forks, 48 open issues and last shipped 3 days ago. Agent-Reach leads on adoption by 2,142% (108,014 vs 4,818 stars). Agent-Reach is written in Python under MIT; chonkie is written in Python under MIT. Agent-Reach has attracted 9% as many forks as stars, chonkie 8%. Agent-Reach 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.

Agent-Reach ★ 108K chonkie ★ 4.8K category AI & Machine Learning

← all 20902 open source comparisons

Side by side

Agent-Reach chonkie
GitHub stars ★ 108K ★ 4.8K
License MIT MIT
Written in Python Python
Last push 2026-11-01 2026-10-31
Forks ⑂ 9.6K ⑂ 368
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

full Agent-Reach profile →

pick chonkie if

  • You want the chonkie feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Python
  • You evaluated both and chonkie fits your workflow better

full chonkie profile →

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 chonkie

🦛 Chonkie ✨ The lightweight ingestion library for fast, efficient and robust RAG pipelines Installation • Usage • Chunkers • Integrations • Benchmarks Tired of making your gazillionth chunker? Sick of the overhead of large libraries? Want to chunk your texts quickly and efficiently? Chonkie the mighty hippo is here to help! 🚀 Feature rich : All the CHONKs you'd ever need 🔄 End to end : Fetch, CHONK, refine, embed and ship straight to your vector DB! ✨ Easy to use : Install, Import, CHONK ⚡ Fast : CHONK at the speed of light! zooooom 🪶 Light weight : No bloat, just CHONK 🔌 32+ integrations : Works with your…

read the full chonkie 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 chonkie more popular?

Agent-Reach has 108,014 GitHub stars and chonkie has 4,818. Agent-Reach has the larger community by that measure.

Are Agent-Reach and chonkie free?

Both are open source. Agent-Reach is licensed under MIT and chonkie under MIT. Neither carries a licence fee.

What is the difference between Agent-Reach and chonkie?

Agent-Reach is written in Python and chonkie 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 chonkie?

Choose Agent-Reach if you want the larger community (108,014 stars) or its MIT licence terms. Choose chonkie if its feature set, stack or MIT licence fits better. Both are self-hostable.