head to head · open source
langgraph vs agentscope
langgraph has 41,863 GitHub stars, 7,069 forks, 786 open issues and last shipped today. agentscope has 31,896 stars, 3,514 forks, 369 open issues and last shipped today. langgraph leads on adoption by 31% (41,863 vs 31,896 stars). langgraph is written in Python under MIT; agentscope is written in Python under Apache-2.0. langgraph has attracted 17% as many forks as stars, agentscope 11%. langgraph was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), 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.
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Side by side
| langgraph | agentscope | |
|---|---|---|
| GitHub stars | ★ 42K | ★ 32K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-18 | 2026-09-18 |
| Forks | ⑂ 7.1K | ⑂ 3.5K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick langgraph if
- You weight community size — 42K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
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
About langgraph
LangGraph is a low level Python orchestration framework for building stateful, long running agents, aimed at developers and platform teams who need durable execution, human in the loop control, and persistent memory instead of a turnkey agent application.
read the full langgraph 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 →
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Frequently asked questions
Is langgraph or agentscope more popular?
langgraph has 41,863 GitHub stars and agentscope has 31,896. langgraph has the larger community by that measure.
Are langgraph and agentscope free?
Both are open source. langgraph is licensed under MIT and agentscope under Apache-2.0. Neither carries a licence fee.
What is the difference between langgraph and agentscope?
langgraph 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, langgraph or agentscope?
Choose langgraph if you want the larger community (41,863 stars) or its MIT licence terms. Choose agentscope if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.