head to head · open source
Agent-Reach vs langroid
Agent-Reach has 108,502 GitHub stars, 9,679 forks, 137 open issues and last shipped 4 days ago. langroid has 4,125 stars, 431 forks, 52 open issues and last shipped 2 days ago. Agent-Reach leads on adoption by 2,530% (108,502 vs 4,125 stars). Agent-Reach is written in Python under MIT; langroid is written in Python under MIT. Agent-Reach has attracted 9% as many forks as stars, langroid 10%. langroid 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
| Agent-Reach | langroid | |
|---|---|---|
| GitHub stars | ★ 109K | ★ 4.1K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-11-01 | 2026-11-03 |
| Forks | ⑂ 9.7K | ⑂ 431 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Agent-Reach if
- You weight community size — 109K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick langroid if
- You want the langroid feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and langroid 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 langroid
Documentation · Examples Repo · Discord · Contributing Langroid is an intuitive, lightweight, extensible and principled Python framework to easily build LLM powered applications, from CMU and UW Madison researchers. You set up Agents, equip them with optional components (LLM, vector store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. This Multi Agent paradigm is inspired by the Actor Framework (but you do not need to know anything about this!). Langroid is a fresh take on LLM app development, where considerable thought has gone…
read the full langroid overview →
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Frequently asked questions
Is Agent-Reach or langroid more popular?
Agent-Reach has 108,502 GitHub stars and langroid has 4,125. Agent-Reach has the larger community by that measure.
Are Agent-Reach and langroid free?
Both are open source. Agent-Reach is licensed under MIT and langroid under MIT. Neither carries a licence fee.
What is the difference between Agent-Reach and langroid?
Agent-Reach is written in Python and langroid 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 langroid?
Choose Agent-Reach if you want the larger community (108,502 stars) or its MIT licence terms. Choose langroid if its feature set, stack or MIT licence fits better. Both are self-hostable.