head to head · open source

Agent-Reach vs Mem0

Agent-Reach has 82,763 GitHub stars, 7,236 forks, 137 open issues and last shipped 3 days ago. Mem0 has 65,505 stars, 7,683 forks, 742 open issues and last shipped yesterday. Agent-Reach leads on adoption by 26% (82,763 vs 65,505 stars). Agent-Reach is written in Python under MIT; Mem0 is written in Python under Apache-2.0. Agent-Reach has attracted 9% as many forks as stars, Mem0 12%. Mem0 was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (python), 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 ★ 83K Mem0 ★ 66K category AI & Machine Learning

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Side by side

Agent-Reach Mem0
GitHub stars ★ 83K ★ 66K
License MIT Apache-2.0
Written in Python Python
Last push 2026-09-15 2026-09-17
Forks ⑂ 7.2K ⑂ 7.7K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agent-Reach if

  • You weight community size — 83K 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 Mem0 if

  • You want the Mem0 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 Mem0 fits your workflow better

full Mem0 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 Mem0

Mem0 is an open source memory layer for AI agents and applications, designed to store, retrieve, and manage persistent context across interactions. It lives in the Python based AI development ecosystem and provides infrastructure that enables agents and apps to remember user preferences, conversation history, and state over time—moving beyond ephemeral chat sessions toward truly adaptive systems.

read the full Mem0 overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K 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 daily_stock_analysis Agent-Reach vs LiteLLM Agent-Reach vs Multica

Frequently asked questions

Is Agent-Reach or Mem0 more popular?

Agent-Reach has 82,763 GitHub stars and Mem0 has 65,505. Agent-Reach has the larger community by that measure.

Are Agent-Reach and Mem0 free?

Both are open source. Agent-Reach is licensed under MIT and Mem0 under Apache-2.0. Neither carries a licence fee.

What is the difference between Agent-Reach and Mem0?

Agent-Reach is written in Python and Mem0 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 Mem0?

Choose Agent-Reach if you want the larger community (82,763 stars) or its MIT licence terms. Choose Mem0 if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.