ZeptoClaw

Fast, small, secure, and local-first personal AI assistant infrastructure.

$ zeptoclaw agent --stream -m "Analyze our API for security issues"

🤖 ZeptoClaw — Streaming analysis...

  [web_fetch]        Fetching API docs...
  [shell]            Running integration tests...
  [longterm_memory]  Storing findings...

→ Found 12 endpoints, 3 missing auth headers, 1 open redirect
→ Saved findings to long-term memory under "api-audit"

✓ Analysis complete in 4.2s

ZeptoClaw is one Rust binary for running personal AI agents locally, at the edge, or on a VPS — with tools, memory, channels, providers, and sandboxed autonomy built in. We studied the best AI assistants — and their tradeoffs: OpenClaw's integrations without the large TypeScript app footprint, NanoClaw's container-isolated simplicity without narrowing to a tiny assistant core, NemoClaw's OpenShell guardrails without the Docker/k3s footprint, and PicoClaw's edge efficiency with Rust's safety and runtime controls.

Why ZeptoClaw

We studied what works — and what doesn't.

OpenClaw proved a personal AI assistant can grow into a broad integration and skills ecosystem. NanoClaw proved container isolation can be simple enough to understand and customize. NemoClaw proved managed guardrails matter — policy-gated sandboxes, routed inference, credential injection, channel messaging, and digest-verified blueprints. PicoClaw proved edge assistants can run on $10 hardware with a Go binary under 10MB of RAM.

ZeptoClaw took notes. The integrations, the security, the governance, the size discipline — without the tradeoffs each one made. One 6MB Rust binary that starts in 50ms, uses 6MB of RAM, and ships with container isolation, prompt injection detection, and a circuit breaker provider stack.

	OpenClaw	NemoClaw	NanoClaw	PicoClaw	ZeptoClaw
Core shape	Broad TypeScript assistant + skills ecosystem	OpenClaw managed through OpenShell	Small TypeScript Claude assistant	Go edge assistant	Single Rust binary
Footprint focus	Integration breadth	Docker/k3s guardrails, ~2.4GB sandbox image	~500-line core

Any VPS

curl -fsSL https://zeptoclaw.com/setup.sh | bash

Installs the binary and prints next steps. Run zeptoclaw onboard to configure providers and channels.

Providers

ZeptoClaw supports 18 LLM providers. All OpenAI-compatible endpoints work out of the box.

Configure in ~/.zeptoclaw/config.json or via environment variables:

{
  "providers": {
    "openrouter": { "api_key": "sk-or-..." },
    "ollama": { "api_key": "ollama" }
  },
  "agents": { "defaults": { "model": "anthropic/claude-sonnet-4" } }
}

export ZEPTOCLAW_PROVIDERS_GROQ_API_KEY=gsk_...

Any provider's base URL can be overridden with api_base for proxies or self-hosted endpoints. See the provider docs for full details.

Features

Core

Channels & Integration

Security & Ops

Full documentation — zeptoclaw.com/docs covers configuration, environment variables, CLI reference, deployment guides, and more.

Inspired By

ZeptoClaw is inspired by projects in the open-source AI agent ecosystem — OpenClaw, NemoClaw, NanoClaw, and PicoClaw — each taking a different approach to the same problem. NemoClaw's policy model, routed inference, credential boundary, and digest-verified blueprint flow influenced our security thinking. ZeptoClaw's contribution is Rust's memory safety, async performance, and configurable isolation for local-first, edge, and production multi-tenant deployments — all in a 6MB binary that runs where Docker containers can't.

Usage

# CLI agent (one-shot or streaming)
zeptoclaw agent -m "Summarize this repo"
zeptoclaw agent --stream -m "Explain async Rust"
zeptoclaw agent --template coder -m "Add error handling to main.rs"

# Multi-channel gateway
zeptoclaw gateway                    # Telegram, Slack, Discord, etc.
zeptoclaw gateway --containerized    # With container isolation per request

# Memory, secrets, profiles
zeptoclaw memory set project:name "ZeptoClaw" --category project
zeptoclaw secrets encrypt
zeptoclaw hand activate researcher

# Batch, diagnostics, self-update
zeptoclaw batch --input prompts.txt --output results.jsonl
zeptoclaw doctor                     # Diagnose config/provider issues
zeptoclaw update                     # Self-update to latest release

Development

# Build
cargo build

# Run all tests (~3,900 total)
cargo nextest run --lib

# Lint and format (required before every PR)
cargo clippy -- -D warnings
cargo fmt -- --check

See CLAUDE.md for full architecture reference, AGENTS.md for coding guidelines, and docs/ for benchmarks, multi-tenant deployment, and performance guides.

Zepto Stack

ZeptoClaw is part of the Zepto stack — a modular local-first system for running on-device AI agents in production.

ZeptoPM        — orchestration, supervision, retries, job lifecycle
    │
    │  create(spec) + spawn(worker, args, env)
    ▼
ZeptoCapsule   — capsule creation, process isolation, resource enforcement
    │
    │  fork/namespace/microVM + stdio transport
    ▼
ZeptoClaw      — LLM calls, tool use, artifact production
    │
    └── JSON-line IPC over stdin/stdout back to ZeptoPM

Contributing

We welcome contributions! Please read CONTRIBUTING.md for:

• How to set up your fork and branch from upstream
• Issue-first workflow (open an issue before coding)
• Pull request process and quality gates
• Guides for adding new tools, channels, and providers

License

Apache 2.0 — see LICENSE

Disclaimer

ZeptoClaw is a pure open-source software project. It has no token, no cryptocurrency, no blockchain component, and no financial instrument of any kind. This project is not affiliated with any token or financial product.

ZeptoClaw — Local-first personal AI assistant infrastructure in one Rust binary.

Built by Aisar Labs

For commercial licensing, enterprise support, or managed hosting inquiries: qaiyyum@aisar.ai