Index / nanobot · updated Sep 3, 2026

nanobot

HKUDS/nanobot · healthy · rank 3 of 43 by stars

An ultra-lightweight, self-hosted personal AI agent framework from HKUDS with a readable Python core, WebUI/TUI, memory, MCP, and multi-agent workflows. It positions itself as the lean, hackable alternative to heavier agent harnesses like OpenClaw.

#python#self-hosted#personal-agent#mcp#lightweight
Compare vs OpenClaw
GitHub ↗

Facts

Repository

Contributors434
Open issues758
Last commitAug 30, 2026
Release cadence~15 days
Latest releasev0.3.0

Runtime

LanguagePython
Memory1.5 MB
Boot time8 ms
Deploymentself-hosted · desktop · cloud
Setup difficultyLow
Plugin ecosystemEmerging

Posture

LicenseMIT
Local-firstYes
Cloud dependencyOptional
Multi-userNo
Privacy postureStrong

Community

Sentiment72% positive
Reddit mentions1
Web results10

Security breakdown

Composite 62 / 100 · how these are scored

Sandboxing4 / 10

higher is safer

API security6 / 10

higher is safer

Network isolation4 / 10

higher is safer

Telemetry safety8 / 10

higher is safer

Shell access risk7 / 10

higher is riskier

Model access

Read from the repository, not written by a model · 74 files examined

5 providers · gateway support

Direct
AnthropicAzure OpenAIAWS BedrockGroqOpenAI
Gateway
LiteLLMOpenRouter
Compatible
OpenAI-compatible

Pinned models

gpt-4oOpenAI
gpt-4.1OpenAI

claude-opus-4-7 released 2026-04-16 — 5 months old (from the public model catalogue)

Pin last edited 10 days ago

Several defaults are pinned; the project picks one per provider rather than shipping a single default.

Evidence

Decision

Why choose nanobot over OpenClaw?

Why choose this

  • Much smaller, more readable codebase that is easy to audit and modify
  • Lower resource footprint and faster startup for personal use
  • Simple pip install with WebUI, TUI, and gateway modes out of the box

Tradeoffs

  • Smaller ecosystem and fewer community skills/integrations
  • Weaker sandboxing and isolation guarantees than container-based setups
  • Less proven at scale for long-running production deployments

Best fit

  • Users wanting a small, readable Python agent core to hack on
  • Self-hosters running personal assistants via WebUI, terminal, or chat apps
  • Builders needing MCP integrations and multi-agent delegation without heavy infra

Avoid if

  • You need strong container-level sandboxing out of the box
  • You want a mature plugin marketplace and large ecosystem
  • You require enterprise-grade multi-user access controls
Good Confidence78%

Strong evidence from the README, PyPI packaging, CI, and active commit history confirms an actively maintained, lightweight agent framework. Sentiment evidence is thin (only one irrelevant Reddit match), so community and security scores carry moderate uncertainty.

AI layer reviewed Aug 24, 2026 · how this is written

Star activity

47,685 stars today

Overview

nanobot is an ultra-lightweight, open-source personal AI agent framework from HKUDS, written in Python (3.11+) and distributed via PyPI as nanobot-ai. It runs as a WebUI, terminal UI, or chat-app gateway and packs tools, long-term memory, MCP integrations, model routing, multi-agent delegation, scheduled automation, and an OpenAI-compatible API into a deliberately small and readable core. It is MIT-licensed, ships with CI, multilingual docs, and an active Discord community.

Compared to OpenClaw, nanobot trades ecosystem breadth and hardened isolation for simplicity and hackability: installation is a single pip command, the gateway can run as a long-lived service (nanobot gateway), and the codebase is small enough for a single developer to audit. Recent commits show heavy investment in the TUI experience (session states, draft preservation, Ctrl+C handling) and execution safeguards (command guard toggles in full-access mode), indicating rapid but somewhat fluid development. It is best suited to self-hosters and tinkerers who want a lean personal agent they can fully understand, rather than a batteries-included platform.

Nominate a clone

Add a new Claw

Paste a GitHub repository and tell us why it belongs on the tracker.

Opens a prefilled issue on GitHub — every nomination is public. Comfortable with a PR? Adding the repo to projects.json is faster.