Openfang

OpenFang The Agent Operating System

Open-source Agent OS built in Rust. 137K LOC. 14 crates. 1,767+ tests. Zero clippy warnings. One binary. Battle-tested. Agents that actually work for you.

Documentation • Quick Start • Twitter / X

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> v0.5.10 (April 2026) > > OpenFang is feature complete but still pre-1.0. Expect rough edges and breaking changes between minor versions. We ship fast and fix fast. Pin to a specific commit for production use until v1.0. Report issues here.

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What is OpenFang?

OpenFang is an open-source Agent Operating System. Not a chatbot framework. Not a Python wrapper around an LLM. Not a "multi-agent orchestrator." A full operating system for autonomous agents, built from scratch in Rust.

Traditional agent frameworks wait for you to type something. OpenFang runs autonomous agents that work for you: on schedules, 24/7, building knowledge graphs, monitoring targets, generating leads, managing your social media, and reporting results to your dashboard.

The entire system compiles to a single ~32MB binary. One install, one command, your agents are live.

curl -fsSL https://openfang.sh/install | sh
openfang init
openfang start
# Dashboard live at http://localhost:4200

Windows

irm https://openfang.sh/install.ps1 | iex
openfang init
openfang start

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Hands: Agents That Actually Do Things

"Traditional agents wait for you to type. Hands work for you."

Hands are OpenFang's core innovation. Pre-built autonomous capability packages that run independently, on schedules, without you having to prompt them. This is not a chatbot. This is an agent that wakes up at 6 AM, researches your competitors, builds a knowledge graph, scores the findings, and delivers a report to your Telegram before you've had coffee.

Each Hand bundles:

• HAND.toml: manifest declaring tools, settings, requirements, and dashboard metrics.
• System Prompt: multi-phase operational playbook. Not a one-liner. These are 500+ word expert procedures.
• SKILL.md: domain expertise reference injected into context at runtime.
• Guardrails: approval gates for sensitive actions (e.g. Browser Hand requires approval before any purchase).

All compiled into the binary. No downloading, no pip install, no Docker pull.

The 7 Bundled Hands

| Hand | What It Actually Does | |------|----------------------| | Clip | Takes a YouTube URL, downloads it, identifies the best moments, cuts them into vertical shorts with captions and thumbnails, optionally adds AI voice-over, and publishes to Telegram and WhatsApp. 8-phase pipeline. FFmpeg + yt-dlp + 5 STT backends. | | Lead | Runs daily. Discovers prospects matching your ICP, enriches them with web research, scores 0-100, deduplicates against your existing database, and delivers qualified leads in CSV/JSON/Markdown. Builds ICP profiles over time. | | Collector | OSINT grade intelligence. You give it a target (company, person, topic). It monitors continuously: change detection, sentiment tracking, knowledge graph construction, and critical alerts when something important shifts. | | Predictor | Superforecasting engine. Collects signals from multiple sources, builds calibrated reasoning chains, makes predictions with confidence intervals, and tracks its own accuracy using Brier scores. Has a contrarian mode that deliberately argues against consensus. | | Researcher | Deep autonomous researcher. Cross-references multiple sources, evaluates credibility using CRAAP criteria (Currency, Relevance, Authority, Accuracy, Purpose), generates cited reports with APA formatting, supports multiple languages. | | Twitter | Autonomous Twitter/X account manager. Creates content in 7 rotating formats, schedules posts for optimal engagement, responds to mentions, tracks performance metrics. Has an approval queue, so nothing posts without your OK. | | Browser | Web automation agent. Navigates sites, fills forms, clicks buttons, handles multi-step workflows. Uses Playwright bridge with session persistence. Mandatory purchase approval gate: it will never spend your money without explicit confirmation. |

# Activate the Researcher Hand. It starts working immediately.
openfang hand activate researcher

# Check its progress anytime
openfang hand status researcher

# Activate lead generation on a daily schedule
openfang hand activate lead

# Pause without losing state
openfang hand pause lead

# See all available Hands
openfang hand list

Build your own. Define a HAND.toml with tools, settings, and a system prompt. Publish to FangHub.

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OpenFang vs The Landscape

Benchmarks: Measured, Not Marketed

All data from official documentation and public repositories, February 2026.

Cold Start Time (lower is better)

ZeroClaw   ██░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   10 ms
OpenFang   ██████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  180 ms    ★
LangGraph  █████████████████░░░░░░░░░░░░░░░░░░░░░░░░░  2.5 sec
CrewAI     ████████████████████░░░░░░░░░░░░░░░░░░░░░░  3.0 sec
AutoGen    ██████████████████████████░░░░░░░░░░░░░░░░░  4.0 sec
OpenClaw   █████████████████████████████████████████░░  5.98 sec

Idle Memory Usage (lower is better)

ZeroClaw   █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    5 MB
OpenFang   ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   40 MB    ★
LangGraph  ██████████████████░░░░░░░░░░░░░░░░░░░░░░░░░  180 MB
CrewAI     ████████████████████░░░░░░░░░░░░░░░░░░░░░░░  200 MB
AutoGen    █████████████████████████░░░░░░░░░░░░░░░░░░  250 MB
OpenClaw   ████████████████████████████████████████░░░░  394 MB

Install Size (lower is better)

ZeroClaw   █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  8.8 MB
OpenFang   ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   32 MB    ★
CrewAI     ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  100 MB
LangGraph  ████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  150 MB
AutoGen    ████████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░  200 MB
OpenClaw   ████████████████████████████████████████░░░░  500 MB

Security Systems (higher is better)

OpenFang   ████████████████████████████████████████████   16      ★
ZeroClaw   ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░    6
OpenClaw   ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    3
AutoGen    █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    2
LangGraph  █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    2
CrewAI     ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    1

Channel Adapters (higher is better)

OpenFang   ████████████████████████████████████████████   40      ★
ZeroClaw   ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░   15
OpenClaw   █████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   13
CrewAI     ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    0
AutoGen    ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    0
LangGraph  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    0

LLM Providers (higher is better)

ZeroClaw   ████████████████████████████████████████████   28
OpenFang   ██████████████████████████████████████████░░   27      ★
LangGraph  ██████████████████████░░░░░░░░░░░░░░░░░░░░░   15
CrewAI     ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   10
OpenClaw   ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░   10
AutoGen    ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░    8

Feature-by-Feature Comparison

| Feature | OpenFang | OpenClaw | ZeroClaw | CrewAI | AutoGen | LangGraph | |---------|----------|----------|----------|--------|---------|-----------| | Language | Rust | TypeScript | Rust | Python | Python | Python | | Autonomous Hands | 7 built-in | None | None | None | None | None | | Security Layers | 16 discrete | 3 basic | 6 layers | 1 basic | Docker | AES enc. | | Agent Sandbox | WASM dual-metered | None | Allowlists | None | Docker | None | | Channel Adapters | 40 | 13 | 15 | 0 | 0 | 0 | | Built-in Tools | 53 + MCP + A2A | 50+ | 12 | Plugins | MCP | LC tools | | Memory | SQLite + vector | File-based | SQLite FTS5 | 4-layer | External | Checkpoints | | Desktop App | Tauri 2.0 | None | None | None | Studio | None | | Audit Trail | Merkle hash-chain | Logs | Logs | Tracing | Logs | Checkpoints | | Cold Start | auto-wipes API keys from memory the instant they're no longer needed. | | 7 | **OFP Mutual Authentication** | HMAC-SHA256 nonce-based, constant-time verification for P2P networking. | | 8 | **Capability Gates** | Role based access control. Agents declare required tools, the kernel enforces it. | | 9 | **Security Headers** | CSP, X-Frame-Options, HSTS, X-Content-Type-Options on every response. | | 10 | **Health Endpoint Redaction** | Public health check returns minimal info. Full diagnostics require authentication. | | 11 | **Subprocess Sandbox** | env_clear() + selective variable passthrough. Process tree isolation with cross-platform kill. | | 12 | **Prompt Injection Scanner** | Detects override attempts, data exfiltration patterns, and shell reference injection in skills. | | 13 | **Loop Guard** | SHA256-based tool call loop detection with circuit breaker. Handles ping-pong patterns. | | 14 | **Session Repair** | 7-phase message history validation and automatic recovery from corruption. | | 15 | **Path Traversal Prevention** | Canonicalization with symlink escape prevention. ../` doesn't work here. | | 16 | GCRA Rate Limiter** | Cost-aware token bucket rate limiting with per-IP tracking and stale cleanup. |

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Architecture

14 Rust crates. 137,728 lines of code. Modular kernel design.

openfang-kernel      Orchestration, workflows, metering, RBAC, scheduler, budget tracking
openfang-runtime     Agent loop, 3 LLM drivers, 53 tools, WASM sandbox, MCP, A2A
openfang-api         140+ REST/WS/SSE endpoints, OpenAI-compatible API, dashboard
openfang-channels    40 messaging adapters with rate limiting, DM/group policies
openfang-memory      SQLite persistence, vector embeddings, canonical sessions, compaction
openfang-types       Core types, taint tracking, Ed25519 manifest signing, model catalog
openfang-skills      60 bundled skills, SKILL.md parser, FangHub marketplace
openfang-hands       7 autonomous Hands, HAND.toml parser, lifecycle management
openfang-extensions  25 MCP templates, AES-256-GCM credential vault, OAuth2 PKCE
openfang-wire        OFP P2P protocol with HMAC-SHA256 mutual authentication
openfang-cli         CLI with daemon management, TUI dashboard, MCP server mode
openfang-desktop     Tauri 2.0 native app (system tray, notifications, global shortcuts)
openfang-migrate     OpenClaw, LangChain, AutoGPT migration engine
xtask                Build automation

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40 Channel Adapters

Connect your agents to every platform your users are on.

Core: Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email (IMAP/SMTP) Enterprise: Microsoft Teams, Mattermost, Google Chat, Webex, Feishu/Lark, Zulip Social: LINE, Viber, Facebook Messenger, Mastodon, Bluesky, Reddit, LinkedIn, Twitch Community: IRC, XMPP, Guilded, Revolt, Keybase, Discourse, Gitter Privacy: Threema, Nostr, Mumble, Nextcloud Talk, Rocket.Chat, Ntfy, Gotify Workplace: Pumble, Flock, Twist, DingTalk, Zalo, Webhooks

Each adapter supports per-channel model overrides, DM/group policies, rate limiting, and output formatting.

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WhatsApp Web Gateway (QR Code)

Connect your personal WhatsApp account to OpenFang via QR code, just like WhatsApp Web. No Meta Business account required.

Prerequisites

• Node.js >= 18 installed (download)
• OpenFang installed and initialized

Setup

1. Install the gateway dependencies:

cd packages/whatsapp-gateway
npm install

2. Configure config.toml:

[channels.whatsapp]
mode = "web"
default_agent = "assistant"

3. Set the gateway URL (choose one):

Add to your shell profile for persistence:

# macOS / Linux
echo 'export WHATSAPP_WEB_GATEWAY_URL="http://127.0.0.1:3009"' >> ~/.zshrc
source ~/.zshrc

Or set it inline when starting the gateway:

export WHATSAPP_WEB_GATEWAY_URL="http://127.0.0.1:3009"

4. Start the gateway:

node packages/whatsapp-gateway/index.js

The gateway listens on port 3009 by default. Override with WHATSAPP_GATEWAY_PORT.

5. Start OpenFang:

openfang start
# Dashboard at http://localhost:4200

6. Scan the QR code:

Open the dashboard → Channels → WhatsApp. A QR code will appear. Scan it with your phone:

> WhatsApp → Settings → Linked Devices → Link a Device

Once scanned, the status changes to connected and incoming messages are routed to your configured agent.

Gateway Environment Variables

| Variable | Description | Default | |----------|-------------|---------| | WHATSAPP_WEB_GATEWAY_URL | Gateway URL for OpenFang to connect to | (empty = disabled) | | WHATSAPP_GATEWAY_PORT | Port the gateway listens on | 3009 | | OPENFANG_URL | OpenFang API URL the gateway reports to | http://127.0.0.1:4200 | | OPENFANG_DEFAULT_AGENT | Agent that handles incoming messages | assistant |

Gateway API Endpoints

| Method | Route | Description | |--------|-------|-------------| | POST | /login/start | Generate QR code (returns base64 PNG) | | GET | /login/status | Connection status (disconnected, qr_ready, connected) | | POST | /message/send | Send a message ({ "to": "5511999999999", "text": "Hello" }) | | GET | /health | Health check |

Alternative: WhatsApp Cloud API

For production workloads, use the WhatsApp Cloud API with a Meta Business account. See the Cloud API configuration docs.

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27 LLM Providers, 123+ Models

3 native drivers (Anthropic, Gemini, OpenAI-compatible) route to 27 providers:

Anthropic, Gemini, OpenAI, Groq, DeepSeek, OpenRouter, Together, Mistral, Fireworks, Cohere, Perplexity, xAI, AI21, Cerebras, SambaNova, HuggingFace, Replicate, Ollama, vLLM, LM Studio, Qwen, MiniMax, Zhipu, Moonshot, Qianfan, Bedrock, and more.

Intelligent routing with task complexity scoring, automatic fallback, cost tracking, and per-model pricing.

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Migrate from OpenClaw

Already running OpenClaw? One command:

# Migrate everything: agents, memory, skills, configs.
openfang migrate --from openclaw

# Migrate from a specific path
openfang migrate --from openclaw --path ~/.openclaw

# Dry run first to see what would change
openfang migrate --from openclaw --dry-run

The migration engine imports your agents, conversation history, skills, and configuration. OpenFang reads SKILL.md natively and is compatible with the ClawHub marketplace.

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OpenAI-Compatible API

Drop-in replacement. Point your existing tools at OpenFang:

curl -X POST localhost:4200/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "researcher",
    "messages": [{"role": "user", "content": "Analyze Q4 market trends"}],
    "stream": true
  }'

140+ REST/WS/SSE endpoints covering agents, memory, workflows, channels, models, skills, A2A, Hands, and more.

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Quick Start

# 1. Install (macOS/Linux)
curl -fsSL https://openfang.sh/install | sh

# 2. Initialize. Walks you through provider setup.
openfang init

# 3. Start the daemon
openfang start

# 4. Dashboard is live at http://localhost:4200

# 5. Activate a Hand. It starts working for you.
openfang hand activate researcher

# 6. Chat with an agent
openfang chat researcher
> "What are the emerging trends in AI agent frameworks?"

# 7. Spawn a pre-built agent
openfang agent spawn coder

Windows (PowerShell)

irm https://openfang.sh/install.ps1 | iex
openfang init
openfang start

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Development

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: RightNow-AI
• Source: RightNow-AI/openfang
• License: Apache-2.0
• Homepage: https://www.openfang.sh/

Install and usage instructions live in the source repository linked above.