head to head · open source

langchain vs agentscope

langchain has 146,562 GitHub stars, 24,508 forks, 492 open issues and last shipped today. agentscope has 31,896 stars, 3,514 forks, 369 open issues and last shipped today. langchain leads on adoption by 359% (146,562 vs 31,896 stars). langchain is written in Python under MIT; agentscope is written in Python under Apache-2.0. langchain has attracted 17% as many forks as stars, agentscope 11%. agentscope 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.

langchain ★ 147K agentscope ★ 32K category AI & Machine Learning

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Side by side

langchain agentscope
GitHub stars ★ 147K ★ 32K
License MIT Apache-2.0
Written in Python Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 25K ⑂ 3.5K
Self-hosting Yes Yes
Data ownership Your server Your server

pick langchain if

  • You weight community size — 147K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full langchain profile →

pick agentscope if

  • You want the agentscope 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 agentscope fits your workflow better

full agentscope profile →

About langchain

LangChain is an open source framework for building agents and LLM powered applications, written in Python and released under the MIT license. It lives in the AI and machine learning ecosystem, specifically among AI development platforms, and it works by chaining together interoperable components and third party integrations so that AI application development becomes simpler. The project describes itself as the agent engineering platform, and its abstractions are designed to keep applications working as the underlying technology evolves.

read the full langchain overview →

About agentscope

AgentScope 2.0 is a production ready agent framework written in Python and released under the Apache 2.0 licence. It provides a set of essential abstractions for building agents, and it is designed explicitly for increasingly agentic large language models. Rather than wrapping models in strict prompts and opinionated orchestrations, the framework leans on the reasoning and tool use abilities the models already have, so the agent logic follows rising model capability instead of fighting it. The project lives in the Python AI and machine learning ecosystem, with a documented homepage at docs.agentscope.io and a rep…

read the full agentscope overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K ponytail ★ 141K

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

Frequently asked questions

Is langchain or agentscope more popular?

langchain has 146,562 GitHub stars and agentscope has 31,896. langchain has the larger community by that measure.

Are langchain and agentscope free?

Both are open source. langchain is licensed under MIT and agentscope under Apache-2.0. Neither carries a licence fee.

What is the difference between langchain and agentscope?

langchain is written in Python and agentscope 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, langchain or agentscope?

Choose langchain if you want the larger community (146,562 stars) or its MIT licence terms. Choose agentscope if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.