head to head · open source
nanobot vs agentscope
nanobot has 48,372 GitHub stars, 8,548 forks, 775 open issues and last shipped today. agentscope has 31,992 stars, 3,522 forks, 369 open issues and last shipped 2 days ago. nanobot leads on adoption by 51% (48,372 vs 31,992 stars). nanobot is written in Python under MIT; agentscope is written in Python under Apache-2.0. nanobot has attracted 18% as many forks as stars, agentscope 11%. nanobot was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (chatbot, mcp, multi-agent), 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
| nanobot | agentscope | |
|---|---|---|
| GitHub stars | ★ 48K | ★ 32K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-20 | 2026-09-18 |
| Forks | ⑂ 8.5K | ⑂ 3.5K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick nanobot if
- You weight community size — 48K 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 nanobot
nanobot is an ultra lightweight, open source, self hosted personal AI agent framework written in Python, aimed at individual developers and small teams who want to run their own agent through a browser WebUI, a terminal, or chat apps instead of renting a hosted assistant.
read the full nanobot 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 nanobot or agentscope more popular?
nanobot has 48,372 GitHub stars and agentscope has 31,992. nanobot has the larger community by that measure.
Are nanobot and agentscope free?
Both are open source. nanobot is licensed under MIT and agentscope under Apache-2.0. Neither carries a licence fee.
What is the difference between nanobot and agentscope?
nanobot 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, nanobot or agentscope?
Choose nanobot if you want the larger community (48,372 stars) or its MIT licence terms. Choose agentscope if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.