head to head · open source
Agent-Reach vs code2prompt
Agent-Reach has 108,502 GitHub stars, 9,679 forks, 137 open issues and last shipped 4 days ago. code2prompt has 7,747 stars, 458 forks, 16 open issues and last shipped 2 days ago. Agent-Reach leads on adoption by 1,301% (108,502 vs 7,747 stars). Agent-Reach is written in Python under MIT; code2prompt is written in Rust under MIT. Agent-Reach has attracted 9% as many forks as stars, code2prompt 6%. code2prompt was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (cli), 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.
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Side by side
| Agent-Reach | code2prompt | |
|---|---|---|
| GitHub stars | ★ 109K | ★ 7.7K |
| License | MIT | MIT |
| Written in | Python | Rust |
| Last push | 2026-11-01 | 2026-11-03 |
| Forks | ⑂ 9.7K | ⑂ 458 |
| 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 code2prompt if
- You want the code2prompt feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Rust
- You evaluated both and code2prompt 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 code2prompt
Convert your codebase into a single LLM prompt. Website • Documentation • Discord Code2Prompt is a powerful context engineering tool designed to ingest codebases and format them for Large Language Models. Whether you are manually copying context for ChatGPT, building AI agents via Python, or running a MCP server, Code2Prompt streamlines the context preparation process. ⚡ Quick Install Cargo To enable optional Wayland support (e.g., for clipboard integration on Wayland based systems), use the wayland feature flag: Homebrew SDK with pip 🐍 🚀 Quick Start Once installed, generating a prompt from your codebase is as…
read the full code2prompt overview →
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Frequently asked questions
Is Agent-Reach or code2prompt more popular?
Agent-Reach has 108,502 GitHub stars and code2prompt has 7,747. Agent-Reach has the larger community by that measure.
Are Agent-Reach and code2prompt free?
Both are open source. Agent-Reach is licensed under MIT and code2prompt under MIT. Neither carries a licence fee.
What is the difference between Agent-Reach and code2prompt?
Agent-Reach is written in Python and code2prompt in Rust. 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 code2prompt?
Choose Agent-Reach if you want the larger community (108,502 stars) or its MIT licence terms. Choose code2prompt if its feature set, stack or MIT licence fits better. Both are self-hostable.