AlphaClaw gives OpenClaw a web UI and auto-healing watchdog

AlphaClaw is an open-source setup and operations harness built specifically for OpenClaw. In plain terms, it turns OpenClaw's steep command-line learning curve into an intuitive browser dashboard, letting you spin up a persistent AI agent in minutes and keep it running smoothly for months without touching SSH.

Anyone running OpenClaw in production knows the real headaches: tedious configuration files, manual SSH rescues after a crash, and long-term agent drift. AlphaClaw steps in as a self-hosted management layer designed to automate all that busywork.

What it actually does

AlphaClaw delivers a password-protected web dashboard powered by a lightweight Preact frontend. It organizes your setup across tabs covering gateway health, visual file editing with git diffs, token and cost analytics, model API keys, environment variables, and interactive webhook debugging.

During your first run, a guided onboarding wizard takes over. It walks you through picking models, connecting your GitHub repository, and pairing Telegram or Discord channels. It even automates Google Workspace OAuth and Pub/Sub setup out of the box using gog-cli.

Under the hood, AlphaClaw manages OpenClaw as a monitored child process. Its built-in watchdog watches for crashes and includes loop protection: if OpenClaw crashes three times within 300 seconds, the watchdog triggers openclaw doctor --fix to self-heal and fires an alert to your Telegram or Discord.

To prevent agents from going off the rails over time, AlphaClaw injects AGENTS.md and TOOLS.md into the system prompt on every message. This prompt-hardening layer enforces strict rules: agents cannot perform high-risk tasks like modifying configs or installing packages without explicit user approval.

Every file change must also be explicitly logged with commit summaries. Paired with automatic hourly Git backups to your repository, every single move your agent makes is completely auditable and reversible. A Drift Doctor tool also inspects your workspace to spot drift before it becomes a problem.

How it runs and requirements

Developer chrysb has provided one-click deployment templates on Railway and Render, though you can self-host it on any server you control. The documentation recommends provisioning an instance with at least 8GB of RAM.

Crucially, there is zero vendor lock-in. AlphaClaw does not touch the core runtime of OpenClaw or hide your data behind proprietary APIs. It is purely automation and UI layered on top of standard OpenClaw tooling.

If you ever outgrow AlphaClaw or simply want to ditch the interface, you can eject at any point. Your workspace remains a clean, standard OpenClaw repository that you can immediately continue running from the native CLI.

Why it matters

We think AlphaClaw addresses the single biggest friction point in autonomous agents: turning a fragile developer experiment into reliable, long-running infrastructure.

Many commercial products promise instant AI agent deployment, but they hold your configuration and workflows hostage inside proprietary walled gardens. If those platforms shut down or hike prices, your workflow dies with them. AlphaClaw brings that same click-and-go convenience to your own infrastructure without taking your setup hostage.

If you want the flexibility of OpenClaw without spending two hours wrestling with terminal scripts and debugging unexpected process crashes, AlphaClaw is well worth setting up right now.