Google ADK vs nanobot
Side-by-side comparison of two agent options that often come up together when people are choosing between self-hosted frameworks, managed assistants, and extensible AI tooling.
Open source19k stars
Google ADK
Google's open-source code-first Python toolkit for building and evaluating AI agents
Open source1.3k stars
nanobot
Open-source MCP agent framework for building and deploying AI agents
Category
Google ADK
nanobot
Tagline
Google's open-source code-first Python toolkit for building and evaluating AI agents
Open-source MCP agent framework for building and deploying AI agents
Deployment
Self-Hosted
Self-Hosted
Pricing
Free to use, with optional model or infrastructure costs if you self-host.
Free to use, with optional model or infrastructure costs if you self-host.
Channels
Web, CLI
Telegram, WhatsApp, Slack, Email, QQ, Feishu, Discord
Open source
Yes
Yes
Privacy
Some privacy controls exist, but vendor-hosted infrastructure still handles a meaningful share of the data flow.
Good privacy posture for most teams, especially when self-hosted or carefully configured.
Google ADK pros
- Official Google backing
- Built-in evaluation framework
- Multi-agent orchestration
nanobot pros
- Open source with transparent code and flexible deployment options.
- Strong privacy story for users who care where data runs.
- Good memory and persistence support for ongoing conversations or tasks.
Google ADK cons
- Python-only
- Development framework, not ready-to-use assistant
- Google Gemini API dependency
nanobot cons
- Go ecosystem for AI tooling is smaller than Python/TypeScript
- Lower autonomy — requires more explicit user-initiated workflows
- Community and plugin ecosystem still growing (1.2k stars)
Google ADK gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
nanobot gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
Not sure which one fits you?
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