NanoClaw vs OpenClaw
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A small, container-isolated AI assistant that connects to chat apps and runs on Anthropic's Agent SDK.
Open source · MIT
Self-hosted AI assistant that runs on your own devices and talks to you in your chat apps.
The short answer
Choose NanoClaw if you need…
- Developers who want a small codebase they can read and change
- People who want an assistant on chat apps with container-level isolation
- Users comfortable working with Claude Code to customize their fork
- Anyone who wants separate agents with separate memory per channel
Choose OpenClaw if you need…
- People who want an AI assistant that runs on their own machine rather than a hosted service
- Developers comfortable with Node.js and command-line setup
- Teams that want a shared Gateway deployment, per the README's team deployment option
- Users who want to talk to an assistant through existing messaging apps
Side-by-side
| NanoClaw | OpenClaw | |
|---|---|---|
| Type | AI model / agent | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 31.1k | 394k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Clone and build from source | Install with a package manager |
| Main language | TypeScript | TypeScript |
| Last code update | 4 days ago | 4 days ago |
What each one is
NanoClaw
NanoClaw is an open-source AI assistant you run on your own machine. It connects to messaging apps such as WhatsApp, Telegram, Slack, Discord and others, and each agent runs in its own Linux container so it can only see files you explicitly mount. The README describes it as a smaller alternative to OpenClaw, designed to be read and modified as code rather than configured through many settings.
OpenClaw
OpenClaw is an open-source AI assistant that runs on your own computer and connects to chat services you already use, such as Telegram, Slack, Discord, WhatsApp, and iMessage. A central Gateway process handles sessions, tools, and channel connections, and you can pick which model provider or agent harness it uses. People use it to have a personal assistant that keeps its state, memory, and credentials on their own hardware.
Best for
NanoClaw
- Developers who want a small codebase they can read and change
- People who want an assistant on chat apps with container-level isolation
- Users comfortable working with Claude Code to customize their fork
- Anyone who wants separate agents with separate memory per channel
OpenClaw
- People who want an AI assistant that runs on their own machine rather than a hosted service
- Developers comfortable with Node.js and command-line setup
- Teams that want a shared Gateway deployment, per the README's team deployment option
- Users who want to talk to an assistant through existing messaging apps
Strengths
NanoClaw
- Agents run in containers and only see explicitly mounted files, per the README
- The codebase is described as small, with one process and a handful of files
- Supports many channels and can use Claude, Codex, OpenCode, Cursor or local Ollama models
OpenClaw
- Runs locally, with state, memory, and credentials stored on your own hardware per the README
- Supports many messaging channels and native apps for macOS, iOS, Android, Windows, and Linux
- MIT licensed with no paid tier or hosted service mentioned in the README
Not ideal for
NanoClaw
- Non-technical users who want a finished app with no setup, since install runs shell scripts and may require Docker and Node
- Users on native Windows, since the README lists macOS, Linux and WSL2 for containers
- People who expect a monitoring dashboard or debugging UI, which the README says is intentionally absent
OpenClaw
- People who want a no-setup hosted service: the README says there is no hosted tier, so you run it yourself
- Anyone who cannot safely lock down inbound messages: the README says tools run on the host by default unless sandboxing is configured
- Users who need to expose the Gateway to others without reading the security guide first
Trade-offs
NanoClaw
- Relies on Claude Code and Anthropic's Agent SDK for its default workflow, so it assumes that stack
- Setup and customization depend on Claude Code, and the README says there is no monitoring UI
- Some features, such as the credential gateway and prebuilt image, involve a third-party gateway or optional account
OpenClaw
- Tools run on the host for the main session unless you configure sandboxing, which carries security risk
- Setup involves a Gateway, channels, and model configuration, so it is not a single click for newcomers
- The README is truncated, so some details on specific features and limits are unclear
Getting started
NanoClaw
Clone the repository
git clone https://github.com/nanocoai/nanoclaw.git nanoclaw-v2Enter the directory
cd nanoclaw-v2OpenClaw
Install via npm (if you already manage Node.js)
npm install -g openclaw@latest --allow-scripts=openclawRun onboarding after a direct npm, pnpm, or Bun install
openclaw onboard --install-daemonFrequently asked questions
What is the difference between NanoClaw and OpenClaw?
NanoClaw: A small, container-isolated AI assistant that connects to chat apps and runs on Anthropic's Agent SDK. OpenClaw: Self-hosted AI assistant that runs on your own devices and talks to you in your chat apps. NanoClaw suits developers who want a small codebase they can read and change, while OpenClaw suits people who want an ai assistant that runs on their own machine rather than a hosted service.
Are NanoClaw and OpenClaw free?
NanoClaw: Free and open source. OpenClaw: Free and open source.
Is NanoClaw or OpenClaw more popular?
OpenClaw has more GitHub stars (394k) than NanoClaw (31.1k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to NanoClaw and OpenClaw?
Other options people compare them with include OpenHands, Edict, /brag, Hermes Agent, Ponytail.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.