head to head · open source

Agent-Reach vs contextgem

Agent-Reach has 83,525 GitHub stars, 7,317 forks, 137 open issues and last shipped 5 days ago. contextgem has 2,003 stars, 186 forks, 0 open issues and last shipped 1 months ago. Agent-Reach leads on adoption by 4,070% (83,525 vs 2,003 stars). Agent-Reach is written in Python under MIT; contextgem is written in Python under Apache-2.0. Agent-Reach has attracted 9% as many forks as stars, contextgem 9%. 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 ★ 84K contextgem ★ 2.0K category AI & Machine Learning

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Side by side

Agent-Reach contextgem
GitHub stars ★ 84K ★ 2.0K
License MIT Apache-2.0
Written in Python Python
Last push 2026-09-15 2026-08-13
Forks ⑂ 7.3K ⑂ 186
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 contextgem if

  • You want the contextgem feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and contextgem fits your workflow better

full contextgem 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 contextgem

ContextGem is a Python project in the AI and machine learning category, specifically for AI development platforms. Its tagline and GitHub description present it as a framework for extracting information from documents with large language models. The project is distributed as the contextgem package on PyPI, supports Python 3.10 through 3.14, and is licensed under Apache 2.0.

read the full contextgem overview →

More in AI & Machine Learning

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

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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 contextgem more popular?

Agent-Reach has 83,525 GitHub stars and contextgem has 2,003. Agent-Reach has the larger community by that measure.

Are Agent-Reach and contextgem free?

Both are open source. Agent-Reach is licensed under MIT and contextgem under Apache-2.0. Neither carries a licence fee.

What is the difference between Agent-Reach and contextgem?

Agent-Reach is written in Python and contextgem 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 contextgem?

Choose Agent-Reach if you want the larger community (83,525 stars) or its MIT licence terms. Choose contextgem if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.