nanobot vs LobeHub
Self-hosted AI agents compared
nanobot and lobehub help people build and run AI agents with configurable models, tools, and scheduling. nanobot centers on a Python agent runtime spanning browser, terminal, and chat channels, while lobehub provides a web workspace for organizing agents and shared team workflows.
nanobot: Run a Self-Hosted Personal AI Agent
nanobot is a Python framework for running a personal AI agent through a browser, terminal, or chat apps. It combines model integrations with tools, memory, MCP, and scheduled workflows for people who want a customizable agent they can host themselves.
LobeHub: Organize AI Agents for 24/7 Operations
LobeHub is a TypeScript AI-agent workspace for hiring, scheduling, and getting reports from an AI team, so work can continue while you are away. Its full-stack app uses Next.js and a Vite SPA, with self-hosting options including Docker.
| nanobot | LobeHub | |
|---|---|---|
| Language | Python | TypeScript |
| License | MIT | — |
| Stars | 48.8k | 83.3k |
| Forks | 8.6k | 16k |
| Last analyzed | Oct 3, 2026 | Oct 20, 2026 |
Key differences
- nanobot is a Python framework and runtime; lobehub is a TypeScript web app and workspace.
- nanobot connects to browser, terminal, and multiple chat channels; lobehub emphasizes pages, projects, and shared workspaces.
- nanobot offers session history and long-term memory; lobehub provides structured, editable personal memory.
- nanobot is MIT-licensed; lobehub's metadata says NOASSERTION, while its README identifies a LobeHub Community License.
- nanobot can be installed as a published package or run on local machines and servers; lobehub documents Docker and supported hosting platforms.
- nanobot's listed repository figures are 48.8k stars and 8.6k forks; lobehub's are 83k stars and 16k forks.
Choose nanobot if you…
- want a Python agent runtime with browser, terminal, and chat interfaces.
- need integrations such as an SDK, OpenAI-compatible API, MCP, or scheduled workflows.
- prefer an MIT-licensed project and are prepared to configure a model provider and runtime.
Choose LobeHub if you…
- want a web workspace for organizing agents, projects, and shared team work.
- need an agent builder, collaboration in shared context, and editable personal memory.
- prefer deployment options that include Docker or supported hosting platforms, and can configure a model provider and API key.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.