head to head · open source

Agent-Reach vs code2prompt

Agent-Reach has 83,525 GitHub stars, 7,317 forks, 137 open issues and last shipped 5 days ago. code2prompt has 7,677 stars, 446 forks, 16 open issues and last shipped 2 days ago. Agent-Reach leads on adoption by 988% (83,525 vs 7,677 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.

Agent-Reach ★ 84K code2prompt ★ 7.7K category AI & Machine Learning

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Side by side

Agent-Reach code2prompt
GitHub stars ★ 84K ★ 7.7K
License MIT MIT
Written in Python Rust
Last push 2026-09-15 2026-09-18
Forks ⑂ 7.3K ⑂ 446
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agent-Reach if

  • You weight community size — 84K 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 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

full code2prompt profile →

About Agent-Reach

Agent Reach is an open source Python command line tool that gives AI agents the ability to read and search the wider internet — Twitter/X, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu among others — for developers and agent builders who want that reach without paying for platform APIs.

read the full Agent-Reach overview →

About code2prompt

code2prompt is a Rust command line tool, also shipped as a Python SDK and an MCP server, that ingests a codebase and formats it into a single LLM prompt with a source tree, prompt templating, and token counting, for developers and agent builders who need to hand repository context to ChatGPT, Claude, or GPT.

read the full code2prompt overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

Agent-Reach vs Dify Agent-Reach vs langchain Agent-Reach vs ponytail Agent-Reach vs generative-ai-for-beginners Agent-Reach vs graphify Agent-Reach vs claude-mem Agent-Reach vs ragflow Agent-Reach vs PaddleOCR Agent-Reach vs headroom Agent-Reach vs Mem0 Agent-Reach vs daily_stock_analysis Agent-Reach vs LiteLLM

Frequently asked questions

Is Agent-Reach or code2prompt more popular?

Agent-Reach has 83,525 GitHub stars and code2prompt has 7,677. 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 (83,525 stars) or its MIT licence terms. Choose code2prompt if its feature set, stack or MIT licence fits better. Both are self-hostable.