| title | Getting Started with VisionClaw | ||||
|---|---|---|---|---|---|
| description | Your guided path to mastering VisionClaw - from installation to advanced features. | ||||
| category | tutorial | ||||
| tags |
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| updated-date | 2026-04-09 | ||||
| difficulty-level | beginner |
Welcome to VisionClaw. This guide will take you from zero to visualising your first 3D knowledge graph with AI agents.
Follow these tutorials in order for the best experience:
Understand VisionClaw's purpose, capabilities, and who it's designed for. Learn how it transforms knowledge management with AI agents and 3D visualisation.
- What problems VisionClaw solves
- Key capabilities and differentiators
- Real-world use cases
- Technical foundation overview
Set up VisionClaw on your system with Docker or native installation.
- System requirements (minimum, recommended, enterprise)
- Docker and Docker Compose setup
- GPU acceleration configuration
- Troubleshooting common issues
Build Your First VisionClaw Graph
Create your first 3D knowledge graph and deploy multi-agent workflows — with a quick path (15 min) and a deep path (45 min).
- Start the stack and access the UI at http://localhost:3001
- Connect a GitHub repository, import JSON, or build manually
- Navigate the 3D space with mouse and keyboard
- Enable GPU physics and watch the layout evolve
- Launch AI agents and monitor execution in real-time
Neo4j Basics — OBSOLETE (ADR-11)
Neo4j has been removed. The graph store is now an embedded Oxigraph RDF triple store running in-process inside the Rust backend (W3C SPARQL 1.1, RocksDB-backed). There is no separate database to set up. This tutorial is retained only as a historical reference and is a candidate for deletion.
| Resource | Description |
|---|---|
| API Reference | REST and WebSocket API documentation |
| Architecture | System design and component overview |
| Troubleshooting | Solutions to common problems |
| Configuration | Customise VisionClaw settings |
Before you begin, ensure you have:
- Docker Desktop (v20.10+) or Docker Engine with Compose
- 8GB RAM minimum (16GB recommended)
- Modern browser with WebGL support (Chrome 90+, Firefox 88+, Safari 14+)
- Optional: NVIDIA GPU with CUDA 11.8+ for acceleration
- GitHub Issues - Report bugs or request features
- GitHub Discussions - Community support
- Troubleshooting Guide - Common solutions
Ready to begin? Start with the Overview to understand what VisionClaw can do for you.