$ 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	<10MB RAM	~6MB binary / ~6MB RAM
Tools & memory	100+ skills	OpenClaw tools in sandbox	Minimal, customizable core	Web search, memory, scheduled tasks	33 built-ins + plugins + memory
Providers	Multi-provider ecosystem	Routed managed inference	Claude-focused	Multi-LLM	18 providers
Channels	Broad chat integrations	Telegram/Discord/Slack via OpenShell	WhatsApp-focused	16+ channels	10 active built-ins + plugins
Isolation	Skill/user-permission model	OpenShell: Landlock + seccomp + netns	OS containers	Workspace sandbox	6 runtimes
Runs on $10 HW	Not the target	Not the target	Not the target	Yes	Yes

Security

AI agents execute code. Most frameworks trust that nothing will go wrong.

The OpenClaw ecosystem has seen CVE-2026-25253 (CVSS 8.8 — cross-site WebSocket hijacking to RCE), ClawHavoc (341 malicious skills, 9,000+ compromised installations), and 42,000 exposed instances with auth bypass. ZeptoClaw was built with this threat model in mind.

Layer	What it does
6 Sandbox Runtimes	Docker, Apple Container, Landlock, Firejail, Bubblewrap, or native — per request
Prompt Injection Detection	Aho-Corasick multi-pattern matcher (17 patterns) + 4 regex rules
Secret Leak Scanner	22 regex patterns catch API keys, tokens, and credentials before they reach the LLM
Policy Engine	7 rules blocking system file access, crypto key extraction, SQL injection, encoded exploits
Input Validator	100KB limit, null byte detection, whitespace ratio analysis, repetition detection
Shell Blocklist	Regex patterns blocking reverse shells, `rm -rf`, privilege escalation
SSRF Prevention	DNS pinning, private IP blocking, IPv6 transition guard, scheme validation
Chain Alerting	Detects dangerous tool call sequences (write→execute, memory→execute)
Tool Approval Gate	Require explicit confirmation before executing dangerous tools

Every layer runs by default. No flags to remember, no config to enable.

Install

# One-liner (macOS / Linux)
curl -fsSL https://raw.githubusercontent.com/qhkm/zeptoclaw/main/install.sh | sh

# Homebrew
brew install qhkm/tap/zeptoclaw

# Docker
docker pull ghcr.io/qhkm/zeptoclaw:latest

# Build from source
cargo install zeptoclaw --git https://github.com/qhkm/zeptoclaw

The control panel is an optional compile-time feature. To use zeptoclaw panel or zeptoclaw serve, build/install with --features panel.

Uninstall

# Remove ZeptoClaw state (~/.zeptoclaw)
zeptoclaw uninstall --yes

# Also remove a direct-install binary from ~/.local/bin or /usr/local/bin
zeptoclaw uninstall --remove-binary --yes

# Package-managed installs still use their package manager
brew uninstall qhkm/tap/zeptoclaw
cargo uninstall zeptoclaw

Quick Start

# Interactive setup (walks you through API keys, channels, workspace)
zeptoclaw onboard

# Talk to your agent
zeptoclaw agent -m "Hello, set up my workspace"

# Stream responses token-by-token
zeptoclaw agent --stream -m "Explain async Rust"

# Use a built-in template
zeptoclaw agent --template researcher -m "Search for Rust agent frameworks"

# Process prompts in batch
zeptoclaw batch --input prompts.txt --output results.jsonl

# Start as a Telegram/Slack/Discord/Webhook gateway
zeptoclaw gateway

# With full container isolation per request
zeptoclaw gateway --containerized

Migrate from OpenClaw

Already running OpenClaw? ZeptoClaw can import your config and skills in one command.

# Auto-detect OpenClaw installation (~/.openclaw, ~/.clawdbot, ~/.moldbot)
zeptoclaw migrate

# Specify path manually
zeptoclaw migrate --from /path/to/openclaw

# Preview what would be migrated (no files written)
zeptoclaw migrate --dry-run

# Non-interactive (skip confirmation prompts)
zeptoclaw migrate --yes

The migration command:

Converts provider API keys, model settings, and channel configs
Copies skills to ~/.zeptoclaw/skills/
Backs up your existing ZeptoClaw config before overwriting
Validates the migrated config and reports any issues
Lists features that can't be automatically ported

Supports JSON and JSON5 config files (comments, trailing commas, unquoted keys).

Deploy

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.

Provider	Config key	Setup
Anthropic	`anthropic`	`api_key`
OpenAI	`openai`	`api_key`
OpenRouter	`openrouter`	`api_key`
Google Gemini	`gemini`	`api_key`
Google Vertex AI	`vertex`	ADC or access token
Groq	`groq`	`api_key`
DeepSeek	`deepseek`	`api_key`
xAI (Grok)	`xai`	`api_key`
NVIDIA NIM	`nvidia`	`api_key`
Azure OpenAI	`azure`	`api_key` + `api_base`
AWS Bedrock	`bedrock`	`api_key`
Kimi (Moonshot)	`kimi`	`api_key`
Zhipu (GLM)	`zhipu`	`api_key`
Qianfan (Baidu)	`qianfan`	`api_key`
Novita AI	`novita`	`api_key`
Liquid AI	`liquid`	`api_key`
Ollama	`ollama`	local/keyless
VLLM	`vllm`	local/keyless

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

{
  "providers": {
    "openrouter": { "api_key": "sk-or-..." },
    "ollama": { "api_key": "ollama"

zeptoclaw

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