RsClaw

An AI agent engine that remembers — and gets better the more you use it.
One 15MB binary · 13 channels · 15 LLM providers · Multi-backend agents · OpenCLI-ready · Built in pure Rust.

🇺🇸 English · 🇨🇳 中文 · 🇯🇵 日本語 · 🇰🇷 한국어 · More languages ▾

Most AI agents forget everything between sessions. Every new conversation starts from zero — your preferences, your context, your workflow, all gone.

RsClaw doesn't forget.

Built from scratch in Rust, RsClaw (Crab AI / 螃蟹 AI) persists every interaction through a three-layer memory store (redb + tantivy + hnsw_rs), learns from your usage patterns, and ships as a single 15MB binary running on ~20MB RAM. Four agent lifetime modes (Main/Named/Sub/Task), four execution backends (Native Rust/Claude Code/OpenCode/ACP), 13 messaging channels, 15 LLM providers, A2A cross-machine orchestration — all without a line of Node.js. Drop-in OpenClaw replacement.

💬 Join Community — WeChat / Feishu / QQ / Telegram

Why RsClaw

🧠 Three-layer persistent memory — redb KV + tantivy full-text + hnsw_rs vector search, built in, fully local
🔌 Four agent backends in one gateway — mix Native Rust, Claude Code, OpenCode, and any ACP-compatible agent in a single workflow
🌐 A2A cross-machine orchestration — agents on different machines collaborate via Google A2A v0.3
🪶 15MB binary, ~20MB idle RAM — runs reliably on low-spec servers and edge devices
🔒 Local-first — memory and data stay in ~/.rsclaw/, never leave your machine

Install

👉 New users

# macOS / Linux
curl -fsSL https://app.rsclaw.ai/scripts/install.sh | bash

# Windows (PowerShell)
irm https://app.rsclaw.ai/scripts/install.ps1 | iex

Then initialize:

rsclaw setup      # Initialize ~/.rsclaw/
rsclaw onboard    # Interactive wizard: provider, channels, etc.
rsclaw start

First start downloads the BGE-small-zh embedding model (~91 MB) into ~/.rsclaw/models/bge-small-zh/ — needed for memory semantic search. The download is resumable: interrupted transfers pick up where they left off on the next start. To pre-place the model and skip the first-run download, drop model.safetensors, tokenizer.json, and config.json from BAAI/bge-small-zh-v1.5 into that directory before rsclaw start. The desktop app ships the model bundled — no first-run download needed.

👉 Migrating from OpenClaw

openclaw gateway stop
rsclaw setup      # Detects OpenClaw data, offers one-click import
rsclaw start      # Everything just works — channels, agents, sessions

Your ~/.openclaw/ is never modified. See Migrate from OpenClaw below for details.

Other install options

Desktop app — .dmg / .exe / .deb from Releases
Via Cargo — cargo install rsclaw
From source — git clone https://github.com/rsclaw-ai/rsclaw.git && cd rsclaw && cargo build --release

Channels (13 + Custom)

Channel	Protocol
WeChat Personal	ilink long-poll (QR scan login, voice/image/file/video)
Feishu / Lark	WebSocket (OAuth or appId + appSecret)
WeCom	AI Bot WebSocket
QQ Bot	WebSocket Gateway
DingTalk	Stream Mode WebSocket
Telegram	HTTP long-poll (DM + group, voice/image/file/video)
Discord	Gateway WebSocket
Slack	Socket Mode WebSocket
WhatsApp	Cloud API Webhook
Signal	signal-cli JSON-RPC
LINE	Webhook
Zalo	Webhook
Matrix	HTTP /sync (optional E2EE)
Custom	Webhook POST to `/hooks/{name}`

All channels support: DM/group policy (open/pairing/allowlist), health monitoring, message retry, pairing codes (8-char, 1hr TTL), streaming modes, file upload confirmation.

LLM Providers (15+)

Qwen, DeepSeek, Kimi, Zhipu (GLM), MiniMax, Doubao (ByteDance), SiliconFlow, GateRouter, OpenRouter, Anthropic, OpenAI, Gemini, xAI (Grok), Groq, Ollama, or any OpenAI-compatible API.

Features: failover with exponential backoff, model fallback chains, thinking budget, Responses API + completions + Ollama native.

Key Features

Built-in Tools (36)

File read/write/search, shell exec (with safety rules), web search/fetch/download, CDP browser automation (50+ actions), memory CRUD, document extraction/creation (PDF/DOCX/XLSX/PPTX), image/video generation, voice STT (Whisper/SenseVoice), TTS, computer_use, cron jobs (recurring + one-shot timer), multi-agent spawn/task, clarify (interactive Q&A), anycli (structured web data extraction).

Pre-parsed Commands (40+)

Local commands that bypass the LLM — zero token cost, sub-millisecond:

/run <cmd>    Shell exec (pipes, redirects)     /search <q>   Web search
/help         Show commands                      /status       Gateway status
/clear        Clear session                      /compact      Compress + save memory
/ctx <text>   Add session context                /btw <q>      Side-channel quick query
/remember     Save to long-term memory           /recall       Search memory
/model <name> Switch model                       /cron list    List cron jobs

Browser Automation (CDP)

Built-in headless Chrome — no ChromeDriver, no Playwright, no Node.js:

50+ actions: open, snapshot, click, fill, scroll, screenshot, evaluate, annotate, capture_video, etc.
Accessibility tree snapshots with @e1 refs for LLM interaction
Semantic locators: getbytext, getbyrole, getbylabel
One-click video download: rsclaw browser download-video <url>
Auth persistence: state save/load for login session reuse
Memory-adaptive instance limits, 5-min idle timeout, crash auto-restart
CLI: rsclaw browser open/snapshot/click/screenshot/... (full agent-browser parity)

AnyCLI — Structured Web Data

Built-in anycli integration. Turn any website into structured CLI output with declarative YAML adapters:

rsclaw anycli run hackernews top --format table limit=10
rsclaw anycli run bilibili hot --format markdown
rsclaw anycli run github-trending repos language=rust
rsclaw anycli search zhihu        # search community hub
rsclaw anycli install zhihu       # install adapter

Built-in adapters: hackernews, bilibili, github-trending, arxiv, wikipedia. Community hub at anycli.org. Agent uses anycli tool automatically when structured data is available — cleaner than web_fetch.

Long-term Memory

Three-layer storage: redb (hot KV), tantivy (full-text search), hnsw_rs (vector similarity). Session compaction at 80% context window, /compact manual compression with memory save, /clear preserves conversation summary.

Multi-Agent Architecture

Four agent types with up to 4-layer delegation:

Type	Created by	Lifetime	Persisted
Main	System	Forever	Config (`default: true`)
Named	User	Permanent	Config file (survives restart)
Sub	LLM	Session	Memory only (gone on restart)
Task	LLM	One-shot	Auto-destroyed after completion

Main ──spawn──→ Named "pm" (persistent, in config)
                 └─spawn──→ Sub "analyst" (temporary)
                              ├─task──→ Task "search-jd" (parallel)
                              └─task──→ Task "search-tb" (parallel)

Each agent can use a different execution backend:

Backend	Description
Native Rust	Built-in LLM runtime (default, fastest)
Claude Code	Claude Agent SDK via ACP protocol
OpenCode	Open-source coding agent
ACP	Any Agent Client Protocol compliant agent

{
  agents: {
    list: [
      { id: "main", default: true, model: { primary: "qwen-plus" } },
      { id: "coder", model: { primary: "deepseek-chat", toolset: "code" },
        claudecode: { command: "claude-agent-acp" } },  // uses Claude Code backend
    ],
    external: [
      { id: "gpu-worker", url: "http://gpu-server:18888", token: "${TOKEN}" },
    ],
  },
}

Collaboration modes: sequential (chain), parallel (fan-out), orchestrated (LLM-driven agent_<id> tool calls).

Permission model:

Toolset per agent: minimal (12 tools) / web / code / standard (16) / full (all)
Exec safety: 50+ global deny patterns apply to ALL agents (cannot be bypassed)
Main cannot be killed; Named/Sub/Task can be killed by their creator
Agents cannot communicate upward or sideways — delegation is strictly top-down

A2A Protocol

Implements Google A2A v0.3 for cross-network agent collaboration. Auto-discovery via /.well-known/agent.json, JSON-RPC 2.0 task dispatch, streaming support.

Security

Exec safety: 50+ deny patterns (sudo, rm -rf /, .ssh, .env, etc.), configurable deny/confirm/allow
Write sandbox: path isolation + content scanning
File upload: two-layer confirmation (size gate + token gate)
Per-agent permissions: configurable command ACL
Tool loop detection: sliding window (12-call, 8-threshold)

Configuration

{
  gateway: { port: 18888 },
  models: {
    providers: {
      qwen: { apiKey: "${DASHSCOPE_API_KEY}" },
      ollama: { baseUrl: "http://localhost:11434" },
    },
  },
  agents: {
    defaults: {
      model: { primary: "qwen/qwen-turbo" },
      timeoutSeconds: 600,
    },
  },
  channels: {
    telegram: { botToken: "${TELEGRAM_BOT_TOKEN}", dmPolicy: "pairing" },
    feishu: { appId: "cli_xxx", appSecret: "${FEISHU_APP_SECRET}" },
  },
}

All string values support ${VAR} env substitution. Config priority: CLI flag > $RSCLAW_BASE_DIR/rsclaw.json5 > ~/.rsclaw/rsclaw.json5 > ./rsclaw.json5.

CLI

rsclaw setup                       # First-time setup wizard
rsclaw start / stop / restart      # Gateway control
rsclaw status                      # Check status
rsclaw doctor --fix                # Health check
rsclaw configure                   # Interactive config (7 sections)
rsclaw update                      # Auto-update from GitHub
rsclaw tools install chrome        # Install tools (chrome/ffmpeg/node/python/opencode)
rsclaw tools status                # Check tool availability
rsclaw pairing pair / list / revoke
rsclaw channels login wechat       # QR scan login

Migrate from OpenClaw

openclaw gateway stop
rsclaw setup          # detects OpenClaw, offers import
rsclaw start

Import copies config, workspace, and sessions into ~/.rsclaw/. OpenClaw data is never modified. All OpenClaw config fields are supported.

What you gain

	RsClaw	OpenClaw
Binary size	~15MB	~300MB+ (node_modules)
Startup	~26ms	2–5s
Idle memory	~20MB	~1000MB+
Long-term memory	Three-layer (redb + tantivy + hnsw_rs)	—
Self-learning	Learns from your usage patterns	—
Multi-backend agents	Native Rust / Claude Code / OpenCode / ACP	—
A2A cross-machine	Google A2A v0.3	—
Browser automation	Built-in headless Chrome (CDP)	—
Exec safety	50+ deny patterns, deny/confirm/allow	—

FAQ

Can I run RsClaw and OpenClaw simultaneously?
Yes. RsClaw uses port 18888 by default, OpenClaw uses 18789. They have separate data directories (~/.rsclaw/ vs ~/.openclaw/) and can run side by side without conflict.

Will RsClaw modify my OpenClaw data?
Never. Import mode is strictly read-only on ~/.openclaw/. All RsClaw data goes to ~/.rsclaw/.

How do I switch back to OpenClaw?
rsclaw stop && openclaw gateway start. Your ~/.openclaw/ is untouched.

Does it work offline?
Yes — with Ollama for local models, or any OpenAI-compatible local endpoint. Voice STT can also run fully local via Candle Whisper.

Can I use RsClaw in my commercial product?
Yes, freely. RsClaw is dual-licensed under MIT OR Apache-2.0 — you can build proprietary products, run SaaS services, or redistribute modified versions without open-source obligations.

Development

cargo test
RUST_LOG=rsclaw=debug cargo run -- gateway run

# Cross-compile
./scripts/build.sh all     # all platforms
./scripts/build.sh macos   # macOS x86_64 + ARM64
./scripts/build.sh linux   # Linux musl static
./scripts/build.sh windows # Windows MSVC

Architecture

src/
  agent/       Agent runtime, memory, tools, preparse
  channel/     13 channels
  config/      JSON5 loader, schema
  gateway/     Startup, hot reload
  provider/    LLM: Anthropic, OpenAI, Gemini, Ollama, failover
  server/      Axum HTTP, REST API, OpenAI-compat endpoints
  store/       redb + tantivy + hnsw_rs
  browser/     Chrome CDP automation
  a2a/         Google A2A v0.3
  acp/         ACP protocol
  ws/          WebSocket v3

Requirements: Rust 1.91+, macOS / Linux / Windows. Optional: ffmpeg, Chrome.

Support the project

If RsClaw saves you hours, consider:

⭐ Star this repo — helps other developers discover RsClaw
🐛 Report bugs via GitHub Issues
💬 Join the community — WeChat / Feishu / QQ / Telegram
🤝 Contribute — see CONTRIBUTING.md

License

Licensed under either of

Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

What this means

✅ Use freely in personal, commercial, and enterprise projects
✅ Modify and redistribute without any obligation to open-source your changes
✅ Build proprietary products on top of RsClaw
✅ Run as a SaaS service without any licensing requirements
✅ No copyleft — your derivative work stays yours

This is the same dual-license used by the Rust language itself, Tokio, Serde, Axum, and most of the Rust ecosystem.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Built with 🦀 in Rust. Inspired by the OpenClaw community.

Name		Name	Last commit message	Last commit date
Latest commit History 1,092 Commits
.cargo		.cargo
.claude/roles		.claude/roles
.github		.github
docs		docs
examples		examples
scripts		scripts
skills		skills
src		src
tests		tests
tools		tools
ui		ui
.clippy.toml		.clippy.toml
.gitignore		.gitignore
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
Cargo.lock		Cargo.lock
Cargo.toml		Cargo.toml
Cross.toml		Cross.toml
LICENSE-APACHE		LICENSE-APACHE
LICENSE-MIT		LICENSE-MIT
README.md		README.md
build.rs		build.rs
defaults.toml		defaults.toml
rust-toolchain.toml		rust-toolchain.toml
rustfmt.toml		rustfmt.toml

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RsClaw

Why RsClaw

Install

👉 New users

👉 Migrating from OpenClaw

Other install options

Channels (13 + Custom)

LLM Providers (15+)

Key Features

Built-in Tools (36)

Pre-parsed Commands (40+)

Browser Automation (CDP)

AnyCLI — Structured Web Data

Long-term Memory

Multi-Agent Architecture

A2A Protocol

Security

Configuration

CLI

Migrate from OpenClaw

What you gain

FAQ

Development

Architecture

Support the project

License

What this means

Contribution

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