VectorClaw v1.0.0: MCP Server for Anki Vector Robot Control
VectorClaw v1.0.0 is an MCP server that lets OpenClaw control a physical Anki Vector robot. The Vector is a palm-sized robot with tank treads, a lift arm, HD camera, proximity/cliff sensors, touch sensor, speaker, screen face, and WiFi connectivity that can operate cloud-independently with Wire-Pod.
Available Tools
The server provides 23 MCP tools organized into functional categories:
- Speech:
vector_say - Motion:
vector_drive,vector_head,vector_lift - Perception:
vector_look,vector_capture_image - Sensors:
vector_proximity_status,vector_touch_status,vector_pose - Display:
vector_face
How It Works
This enables embodied AI through tool orchestration. Your agent can perceive → reason → act in a loop:
vector_look() → capture image Send to vision model → "What do you see?" Agent decides action based on response vector_drive() or vector_say() → act
The approach allows your assistant to control a physical platform by calling tools rather than requiring a specialized robotics model.
Roadmap
v1.x planned features:
- Async motion control (non-blocking drive with interrupt capability)
- Audio recording from robot microphones
- Multiple robot support
- Personality modes
v2.0 vision: ROS2 integration for SLAM + NAV2, enabling higher-level commands like "go to kitchen" instead of low-level "turn 90°, drive 2m" instructions.
Links
- PyPI: https://pypi.org/project/vectorclaw-mcp/
- ClawHub: https://clawhub.ai/danmartinez78/vectorclaw-mcp
- GitHub: https://github.com/danmartinez78/VectorClaw
📖 Read the full source: r/openclaw
👀 See Also
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Godogen is an open-source pipeline that uses Claude Code skills to generate complete, playable Godot 4 projects from text prompts. It handles architecture design, 2D/3D asset generation, GDScript writing, and visual QA testing, addressing specific engineering bottlenecks like GDScript training data scarcity and build-time vs runtime state issues.
How AI assistants fetch web pages: Nginx log analysis of ChatGPT, Claude, Gemini and others
A developer tested five major AI assistants by prompting them with unique URLs and monitoring Nginx logs, revealing distinct retrieval patterns: ChatGPT, Claude, and Perplexity use dedicated user-agents while Gemini answered from its index without fetching.
OpenClaw Setup on Ubuntu UTM VM with LLM API and Ollama Access
A user successfully configured OpenClaw in a sandboxed Ubuntu VM on an M3 Mac, with access to both local Ollama on macOS and external LLM APIs like Gemini, Claude, and DeepSeek. Sample configuration files and troubleshooting notes are available on GitHub.