Cadenya
Freemium
Developers building agentic workflows
NanoClaw
FreeOpen SourceAPISelf-HostedAgentic
NanoClaw is a self-hosted AI agent framework small enough to audit in eight minutes, designed for individuals who want full ownership without team complexity.
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Get This Tool
License: MIT Any use incl. commercial
Local-run terms: The entire codebase is available on GitHub, and contributions are welcome. The project encourages forking and customization. Users can fork, modify, and run locally without commercial restrictions.
Pricing
- Model
- Free
- Free Tier
- NanoClaw itself is completely free and open source under the MIT license. However, it runs on the Claude Agent SDK, which requires a Claude API key or Claude Code subscription. The cost depends on how much you use it; NanoClaw is designed to be lightweight in token usage, but the underlying AI usage is billed by Anthropic.
Summary
NanoClaw runs personal AI agents inside Linux containers on your own machine, connecting them to messaging platforms like Slack, Discord, and WhatsApp. It sits in the gap between heavyweight agent frameworks built for product teams and simple chatbots—targeting users who need to know exactly what their AI is doing and can't outsource that visibility to a vendor. The whole codebase is 15 files, readable in one sitting, and can connect to Claude via Anthropic's official SDK or OpenAI. It costs nothing. The tradeoff: container isolation is documented, but the README doesn't specify how the agent controls outbound network traffic, leaving potential for data exfiltration through HTTP requests unless you manually configure firewall rules.
Bottom line: *Use this if you need a self-hosted agent you can fully understand; skip it if you need managed security controls out of the box.*
Find your fit
Before you choose NanoClaw
More options in Agent Frameworks. Compare pricing, platforms, and features side by side.
Brain Memory
Free · Open source
Long-term continuity in multi-session coding projects
Pros
- Entire system can be audited by a human or a secondary AI in roughly eight minutes.
- Agents run in Linux containers and can only see what's explicitly mounted; bash access is safe because commands run inside the container, not on your host.
- Natively uses Claude Code via Anthropic's official Claude Agent SDK, with drop-in options for OpenAI, OpenRouter, Google, DeepSeek, and local models.
- Runs as a single Node.js process using real container isolation rather than application-level sandboxing, and is small enough to understand completely.
Cons
- Container filesystem isolation exists, but README doesn't detail network egress controls; if the agent inside the container can make arbitrary outbound HTTP requests, that's a data exfiltration vector that could benefit from deny-all networking and domain allowlisting like other projects.
- The project is young, launched January 31, 2026, and has room to mature in some areas.
- Smaller ecosystem compared to OpenClaw; requires familiarity with CLI and skill commands like /add-telegram for extensions
About
- Platforms
- macOS, Linux, Windows (WSL2); Docker; Node.js 22+ and pnpm 10+
- Languages
- TypeScriptJavaScript
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- April 23, 2026
Best For
Who it's for
- Individuals who want a personal AI assistant that they fully own and control, as opposed to frameworks designed for teams building products that are large, complex, and require significant investment to understand.
- Teams handling sensitive data in regulated environments where audit logging and container isolation are compliance requirements.
- Engineers prioritizing security and auditability over feature breadth
- Users seeking minimal, understandable code they can customize via AI
What it does well
- Teams handling sensitive data in regulated environments—finance, healthcare, legal.
- Personal AI assistants with strong privacy and security requirements
- Running internal operations for AI go-to-market agencies and small teams.
- Educational use for understanding agent architecture
- Developers wanting to audit and customize AI agent code
Integrations
Frequently Asked Questions
- Is NanoClaw free?
- NanoClaw offers a free option. Hosting, model usage, or optional services may have separate costs; check the pricing details and official terms.
- Is NanoClaw open source?
- Yes. NanoClaw is open source — the source repository is at https://github.com/qwibitai/nanoclaw.
- Does NanoClaw have an API?
- Yes. NanoClaw exposes a developer API. See the official documentation at https://nanoclaw.dev for details.
- Can I self-host NanoClaw?
- Yes. NanoClaw supports self-hosting on your own infrastructure.
- When was NanoClaw released?
- NanoClaw was first released in 2026.
- What platforms does NanoClaw support?
- NanoClaw is available on: macOS, Linux, Windows (WSL2); Docker; Node.js 22+ and pnpm 10+.
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NanoClaw is a self-hosted AI agent framework small enough to audit in eight minutes, designed for individuals who want full ownership without team complexity.
NanoClaw runs personal AI agents inside Linux containers on your own machine, connecting them to messaging platforms like Slack, Discord, and WhatsApp. It sits in the gap between heavyweight agent frameworks built for product teams and simple chatbots—targeting users who need to know exactly what their AI is doing and can't outsource that visibility to a vendor. The whole codebase is 15 files, readable in one sitting, and can connect to Claude via Anthropic's official SDK or OpenAI. It costs nothing. The tradeoff: container isolation is documented, but the README doesn't specify how the agent controls outbound network traffic, leaving potential for data exfiltration through HTTP requests unless you manually configure firewall rules.
*Use this if you need a self-hosted agent you can fully understand; skip it if you need managed security controls out of the box.*
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