Custom Command Center App for OpenClaw: React PWA with WebSocket Proxy and Tailscale

A Reddit user (Weird_Night_2176) shared their custom command center app built on top of their OpenClaw gateway. The app replaces their previous WhatsApp-based control method, which was limited by Twilio's 50 messages/day sandbox cap. The setup runs on a Jetson device, serving a React PWA accessible anywhere via Tailscale.
Architecture & Key Components
- WebSocket Proxy: OpenClaw binds to loopback only, so the developer created a lightweight Express proxy server that bridges the WebSocket connection. This allows the React frontend to communicate with the OpenClaw gateway from any device on the Tailscale mesh.
- Frontend: A React Progressive Web App (PWA) served directly from the Jetson.
- Network: Tailscale mesh for secure remote access; the app works on iPhone via Tailscale.
Features of the Command Center
- Live Chat Interface: Direct chat with the AI agent "Bosefus".
- Agent Dashboard: Shows 14 agents with their last task and status.
- Trading Desk: Live Alpaca positions and crypto P&L.
- Crew Run History: Every automated job logged by name.
- Ollama Model Status: Live status from the Orange Pi model server.
- Build Fund Tracker: Tracks savings toward the next hardware upgrade.
- Push Notifications: Replaces WhatsApp for alerts.
Who This Is For
Developers running OpenClaw as an AI agent gateway who need a purpose-built UI beyond command-line or third-party messaging apps, especially those with multiple agents and trading integrations.
Resources
The user mentioned a full build walkthrough coming on YouTube. For now, the Reddit post has details on the architecture and motivation.
📖 Read the full source: r/openclaw
👀 See Also

How to Claim and Extend Anthropic API Credits Using Manifest's Router
A Reddit post details steps to claim up to $200 in free Anthropic API credits and configure Manifest's router to automatically route prompts to cheaper models like Haiku for simple tasks, extending credit lifespan from one month to several.

Running OmniCoder-9B locally with llama.cpp configuration details
A developer achieved 96.7% average HumanEval score with OmniCoder-9B on mid-range hardware using specific llama.cpp flags including --reasoning-budget 0 to disable chain-of-thought output. The setup used a Q6_K quantized model running on an RTX 3080 with 10GB VRAM.

Method for Transferring User Context from ChatGPT to Claude
A Reddit user shares a two-prompt method for extracting a detailed cognitive profile from ChatGPT and creating a portable AI constitution to transfer to Claude, addressing the difficulty of porting between AI systems.

Open-source launch playbook for OSS LLM and local AI projects
An open-source playbook addresses discoverability issues for LLM and local AI projects by providing structured guidance on pre-launch preparation, launch-day execution, and post-launch follow-up. It includes templates and strategies for community distribution, creator outreach, and SEO optimization.