NanoClaw
by NanoCo
A personal AI agent small enough to audit, isolated in a container by default
NanoClaw is an MIT-licensed personal AI agent harness that runs each agent inside a Docker container rather than directly on your machine. Built by NanoCo as a security-focused alternative to OpenClaw, it connects to messaging apps like WhatsApp, Slack and Telegram, keeps persistent memory, and runs scheduled jobs on Anthropic's Claude Agent SDK.
NanoClaw is an open-source AI agent harness created in February 2026 by brothers Gavriel and Lazer Cohen, whose Tel Aviv company NanoCo pivoted from AI marketing to build it. Its premise is deliberately austere: the software hosting a powerful agent should be small enough to read end to end, so the TypeScript codebase spans roughly fifteen core source files against OpenClaw's half-million lines and seventy-plus dependencies. Architecturally it is a three-tier system. A host process routes messages down an entity hierarchy from user to messaging group to agent group to session; two per-session SQLite databases, inbound.db and outbound.db, act as a bridge with single-writer semantics that avoids cross-mount contention and complex IPC; and a per-agent-group Docker container runs the agent itself on Bun and Anthropic's Claude Agent SDK. The security model is isolation rather than permission-checking — agents see only what is explicitly mounted, and credentials never sit in the container as raw API keys because requests route through OneCLI's Agent Vault, which injects authentication at the proxy layer. In March 2026 Docker partnered with NanoCo to run NanoClaw agents inside MicroVM-based Docker Sandboxes for isolation stronger than a process jail. Channels install on demand via /add-<channel> skills and cover WhatsApp, Telegram, Discord, Slack, Microsoft Teams, iMessage, Matrix, Google Chat, Webex, Linear, GitHub, WeChat and email. The project has passed 30,000 GitHub stars and 250,000 downloads; NanoCo raised a $12M seed in May 2026 after turning down a roughly $20M buyout.
A security-minded engineer or platform team that wants a personal or per-employee AI agent they can fully audit and self-host, and refuses to give an agent unbounded access to a host machine.
Container-level OS isolation per agent from a codebase small enough to read, so an agent's blast radius is a mounted workspace rather than your entire filesystem.
At a Glance
- Category
- AI Agents & Orchestration
- Pricing
- Free, Contact for pricing
- Target Market
- CTOs, CISOs, Enterprise Developers, Platform Engineers
- Deployment
- Open-source, Self-hosted
- Founded
- 2026
- Headquarters
- Tel Aviv, Israel
- Customers
- Over 250,000 downloads and 30,500+ GitHub stars; employees at Amazon, Google, Meta, SentinelOne, Accenture and Gap reported as users, though no formal customer deals have been named
Key Features
- ✓Per-agent Docker container isolation
Every agent group runs in its own container with filesystem isolation, so an agent sees only what is explicitly mounted.
- ✓Auditable minimal codebase
Roughly fifteen core source files in TypeScript, deliberately kept small enough that a reviewer can read the whole harness.
- ✓SQLite message bridge
Two per-session databases with single-writer semantics move messages in and out, avoiding cross-mount contention and complex inter-process communication.
- ✓Docker Sandboxes MicroVM support
Optional MicroVM-based sandboxes from the Docker partnership give a stronger isolation boundary than a standard container process jail.
- ✓On-demand channel skills
Messaging channels install individually through /add-<channel> skills rather than shipping built in, keeping the trunk minimal.
- ✓Agent Vault credential injection
Containers never hold raw API keys; OneCLI's Agent Vault injects authentication at the proxy layer on outbound calls.
- ✓Persistent memory and scheduled jobs
Per-agent-group memory via CLAUDE.md plus recurring tasks with script gates that avoid waking containers unnecessarily.
Capabilities
Use Cases
- •Personal assistant over messaging apps
Reach a private agent through WhatsApp or Telegram that retains context and can act on live data safely.
- •One sandboxed agent per employee
NanoCo's enterprise service gives each employee an isolated agent, routing Slack or Teams requests through a bridge and credential vault.
- •Safe autonomous execution
Docker Sandboxes let teams run aggressive modes such as skipping permission prompts because actions stay contained in a disposable MicroVM.
- •Scheduled operational checks
Recurring jobs poll systems or summarize activity on a schedule, gated by scripts so containers wake only when needed.
- •Auditable agent deployment in regulated teams
Security reviewers can read the entire harness before approval, which is impractical with half-million-line alternatives.
Ideal For
Best For
- ✓Running a personal AI assistant reachable from WhatsApp, Telegram, Slack or Discord without exposing the host machine
- ✓Security teams that need to audit an agent harness line by line before allowing it near company data
- ✓Giving individual employees their own sandboxed agent with per-agent workspace, memory and filesystem
- ✓Scheduled recurring automation — periodic checks and jobs that wake an agent only when a script gate passes
- ✓Developers who want Anthropic's Claude Agent SDK wrapped in isolation without adopting a heavyweight framework
Not Ideal For
- ✗Non-technical users — setup requires Node.js 20+, pnpm 10+, Docker Desktop or Engine, and there are no configuration files by design, so customization means editing code
- ✗Teams wanting a managed SaaS product with an SLA; the open-source project is self-hosted and support is a community Discord, with the commercial enterprise service sold separately by NanoCo
- ✗Organizations needing a broad feature roadmap — the maintainers deliberately restrict trunk contributions to security and bug fixes, pushing new capability onto separate skills branches
- ✗Anyone who wants provider choice, since the harness runs directly on Anthropic's Claude Agent SDK and requires a Claude API key or subscription
Integrations
Deployment
Market & Ratings
Over 250,000 downloads and 30,500+ GitHub stars; employees at Amazon, Google, Meta, SentinelOne, Accenture and Gap reported as users, though no formal customer deals have been named
Market Analysis
Pros
- ✓Real OS-level isolation per agent rather than application-level permission checks, which is the specific OpenClaw weakness it was built to fix
- ✓Small enough to audit completely — roughly fifteen core files against competitors' half-million lines and seventy-plus dependencies
- ✓Very broad messaging channel coverage installed on demand, from WhatsApp and Slack through to Matrix, Webex, Linear and WeChat
- ✓Strong strategic validation: Docker and Vercel both invested and Docker shipped a Sandboxes integration, while Andrej Karpathy's endorsement drove adoption
- ✓MIT-licensed with no configuration lock-in, and the full codebase is on GitHub
Cons
- ✗Operationally demanding for a personal assistant — Node.js 20+, pnpm 10+ and Docker Desktop or Engine are all prerequisites, with WSL2 required on Windows
- ✗No configuration files by design, so any customization means editing source code rather than setting an option
- ✗Hard dependency on Anthropic: the harness runs on the Claude Agent SDK, so there is no straightforward provider substitution and running costs are Anthropic's token bills
- ✗Governance is deliberately closed to feature contributions — trunk accepts only security and bug fixes, so requested capabilities land on separate branches or not at all
- ✗The repository carries a substantial open backlog, around 309 issues and 560 open pull requests, which is a maintenance signal worth weighing
- ✗The enterprise service is early — NanoCo was still implementing via forward-deployed engineers with no published pricing and no named customer contracts
Pricing
Open source (MIT)
$0
- ✓Full harness under MIT licence
- ✓All messaging channel skills
- ✓Container isolation
- ✓Persistent memory and scheduled jobs
- ✓Community Discord support
NanoCo enterprise service
Contact for pricing
- ✓Managed per-employee sandboxed agents
- ✓Router and Agent Vault credential handling
- ✓Forward-deployed engineer implementation
- ✓Centralized security policies
The harness itself is free and MIT-licensed, but it is not free to run: NanoClaw executes on Anthropic's Claude Agent SDK and requires either a Claude API key, billed by Anthropic on token consumption, or a Claude Code subscription. You also supply the host machine and Docker runtime. NanoCo separately sells a managed enterprise service that provisions one sandboxed agent per employee with centralized policy, credential vaulting and forward-deployed engineers for implementation; no list pricing for that service has been published, and the company was still booking early enterprise customers as of mid-2026.
Security & Compliance
Connect
Sources
This page was written from 6 sources, 5 on domains other than nanoclaw.dev.
- 1.github.com — nanoclaw
- 2.nanoclaw.dev — nanoclaw.devvendor
- 3.docker.com — nanoclaw docker sandboxes agent security
- 4.techtarget.com — NanoClaw AI agents find a home in Docker Sandboxes
- 5.techcrunch.com — nanoclaw creator turns down 20m buyout offer raises 12m seed
- 6.thenewstack.io — nanoco nanoclaw sandboxed agent
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