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ZeroClaw

ZeroClaw, an open-source AI assistant from zeroclaw-labs, has reached 32,933 GitHub stars with version v0.8.5 released under a dual MIT OR Apache-2.0 license. The Rust-built binary starts in under 20ms, runs on ARM and x86 hardware including Raspberry Pi, and connects to 70+ LLM providers and 30+ channels while enforcing OS-level sandboxes via Landlock, Bubblewrap, Seatbelt, or Docker. The project positions itself as a self-hosted alternative to cloud AI assistants, using the user's own API keys or fully local models such as Ollama.

read4 min views2 publishedOct 5, 2026
ZeroClaw
Image: Openalternative (auto-discovered)

Open Source Alternative to:

32,933stars+57(+0.2%) Last 30 days

  • Last commit 15 hours ago
  • Repository age 8 months
  • Version v0.8.5
- License [Apache-2.0](https://openalternative.co/licenses/apache-2)
- Self-hosted [Yes](https://openalternative.co/collections/self-hosted)
- Repository [zeroclaw-labs/zeroclaw](https://github.com/zeroclaw-labs/zeroclaw)

Most AI assistants are a seat you rent on someone else's infrastructure. ZeroClaw runs as a single native binary on your own machine, using your own API keys or fully local models like Ollama. No cloud seat, no subscription, no ZeroClaw server in the middle.

The binary is built in Rust and starts in under 20ms. It uses less memory than a browser tab and runs on everything from a workstation to a Raspberry Pi, including ARM and x86. There's no Node, JVM, or Python environment to install.

What it connects to:

  • 70+ LLM providers: local options likeLM Studio , llama.cpp, vLLM, andLocalAI , plus hosted providers including Anthropic, OpenAI, Google Gemini, Amazon Bedrock, Mistral, Groq, and any OpenAI-compatible endpoint
  • 30+ channels: Telegram, Discord, WhatsApp, Slack, Signal, iMessage, Matrix, email, IRC, Bluesky, Reddit, Nostr, Notion, webhooks, and more
  • Hardware: GPIO on Raspberry Pi, STM32, Arduino, and ESP32

Security is the default posture, not an add-on.

  • Supervised autonomy: medium-risk actions require your approval before they run; high-risk ones are blocked outright
  • OS-level sandboxes: Landlock, Bubblewrap, Seatbelt, or Docker contain what the agent can touch, enforced by the kernel rather than a prompt
  • Command allowlists: explicit workspace scoping decides what runs and where
  • Tool receipts: every successful tool call can be stamped with an HMAC-SHA256 tag the model cannot forge, making fabricated runs or invented results detectable

YOLO mode exists for trusted dev environments and is strictly opt-in.

The agent supports multiple named agents running from a single daemon, each isolated. Skills package repeatable tasks with their tools. Scheduled jobs, webhook triggers, and channel events all run through the same agent loop inside the same sandbox and allowlists you've scoped. A2A discovery lets agents describe and find one another through the gateway.

With a local model, nothing leaves your machine at all. With a hosted provider, only your prompts go to the provider you chose, using your own key. Dual-licensed MIT OR Apache-2.0.

Every Sunday we deconstruct one proprietary app and pick the best open source alternatives worth switching to.

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