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What is OpenClaw?

OpenClaw is an open-source framework for running autonomous AI agents on your own infrastructure. It handles scheduling, memory, tool use, and more — so your AI agent can work independently around the clock.

How OpenClaw Works

OpenClaw provides the runtime layer that turns a large language model into a persistent, autonomous AI agent. Instead of one-off prompts, OpenClaw gives your agent a workspace, a schedule, and the ability to use tools — creating a self-directed system that can plan, execute, and iterate on tasks without constant human input.

• Workspace Every OpenClaw agent operates inside a dedicated workspace directory. Files, notes, and outputs are organized here, giving the agent persistent storage across sessions.
• Scheduling OpenClaw runs your AI agent on a configurable schedule. It wakes up, checks for pending tasks, works through them, and goes back to sleep — fully automated.
• Memory Agents retain context between sessions through memory files. OpenClaw manages short-term and long-term memory so your agent can build on previous work.
• Tool Use OpenClaw agents can call external tools, APIs, and scripts. Skills define what tools are available, making each agent customizable for different workflows.

At its core, OpenClaw turns an AI model into something closer to a team member: it reads tasks, plans its approach, executes using tools, writes results to the workspace, and logs what it did. All of this happens on your own server — no cloud platform required.

Why Use an OpenClaw Dashboard?

Running OpenClaw from the command line works, but as your agent takes on more tasks, managing everything through config files and terminal commands becomes tedious. An OpenClaw dashboard gives you a visual interface to see what your agent is doing, assign new work, track costs, and adjust its behavior — all without touching the terminal.

A good dashboard turns OpenClaw from a developer tool into a practical productivity system. Instead of reading log files to figure out what happened overnight, you open a browser tab and see a clear timeline. Instead of editing JSON to add a task, you drag a card on a Kanban board.

• Visibility — see your agent's activity, status, and output at a glance
• Task management — create, prioritize, and track tasks visually instead of editing files
• Cost awareness — monitor token usage and spending across AI models in real time
• Configuration — edit your agent's soul, skills, and settings from the browser
• History — review what your agent worked on with calendar and activity views

VidClaw: The Self-Hosted OpenClaw Dashboard

VidClaw is a self-hosted dashboard purpose-built for OpenClaw. It connects directly to your OpenClaw workspace and gives you full control over your AI agent through a clean, real-time web interface. Because it is entirely self-hosted, your data never leaves your server.

• Kanban task board — drag-and-drop task management with Backlog, Todo, In Progress, and Done columns. Your OpenClaw agent picks up tasks automatically.
• Soul editor — edit your agent's persona and operating instructions with version history and one-click revert.
• Skills manager — browse, enable, disable, or create custom skills. Changes are loaded on the next agent session.
• Content browser — view workspace files with markdown preview and syntax highlighting.
• AI cost tracking — per-model token usage, daily and monthly summaries, and rate limit progress bars.
• Activity calendar — monthly view of what your agent worked on each day.
• Real-time updates — WebSocket-powered UI that reflects changes instantly, no polling required.
• Privacy first — binds to localhost only, accessed via SSH tunnel. No accounts, no cloud, no tracking.

Getting Started with OpenClaw and VidClaw

Setting up your self-hosted OpenClaw dashboard takes just a few minutes. Here is how to get VidClaw running alongside your OpenClaw agent:

• Step 1: Install OpenClaw on your server and configure your AI agent workspace.
• Step 2: Clone the VidClaw repository and run the setup script: ./setup.sh
• Step 3: The setup installs dependencies, builds the frontend, and creates a systemd service.
• Step 4: Access your OpenClaw dashboard via SSH tunnel: ssh -L 3333:localhost:3333 root@your-server
• Step 5: Open localhost:3333 in your browser and start managing your AI agent.

VidClaw reads directly from your OpenClaw workspace at ~/.openclaw/workspace/dashboard. There is no database — all data is stored in simple JSON files on your server. Updates are as easy as running ./update.sh.