head to head · open source

Agent-Reach vs langroid

Agent-Reach has 83,525 GitHub stars, 7,317 forks, 137 open issues and last shipped 5 days ago. langroid has 4,103 stars, 401 forks, 52 open issues and last shipped 3 days ago. Agent-Reach leads on adoption by 1,936% (83,525 vs 4,103 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.

Agent-Reach ★ 84K langroid ★ 4.1K category AI & Machine Learning

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Side by side

Agent-Reach langroid
GitHub stars ★ 84K ★ 4.1K
License MIT MIT
Written in Python Python
Last push 2026-09-15 2026-09-17
Forks ⑂ 7.3K ⑂ 401
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 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

full langroid 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 langroid

Langroid is a Python framework for building applications powered by large language models through multiple agents. It comes from researchers at CMU and UW Madison, and it lives in the Python AI development ecosystem. Developers create agents, give them optional components such as a language model, a vector store, and tools or functions, and assign tasks that the agents solve by exchanging messages.

read the full langroid 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 langroid more popular?

Agent-Reach has 83,525 GitHub stars and langroid has 4,103. 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 (83,525 stars) or its MIT licence terms. Choose langroid if its feature set, stack or MIT licence fits better. Both are self-hostable.