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vectorclaw-mcp

MCP tools for Anki Vector: speech, motion, camera, sensors, and automation workflows.

danmartinez780 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install danmartinez78/vectorclaw-mcp

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

VectorClaw MCP

VectorClaw connects OpenClaw to an Anki / Digital Dream Labs Vector robot through MCP. It provides practical robot control primitives for speech, movement, camera capture, and status/sensor reads.

What you can do

  • Speak text with vector_say
  • Move and position with vector_drive, vector_head, vector_lift
  • Capture camera images with vector_look and vector_capture_image
  • Read robot state with vector_status, vector_pose, vector_proximity_status, vector_touch_status
  • Build look → reason → act workflows

Vision requirement for look → reason → act

For see → reason → act workflows, the agent must either be vision-capable itself (e.g., a VLM) or have access to a separate vision model/image-interpretation tool to analyze camera images before choosing actions.

Requirements

  • Vector robot configured and reachable
  • Wire-Pod running
  • SDK configured at ~/.anki_vector/sdk_config.ini
  • VECTOR_SERIAL environment variable set

Quick setup

  1. Install package: pip install vectorclaw-mcp
  2. Configure SDK: python3 -m anki_vector.configure
  3. Export robot serial: export VECTOR_SERIAL=your-serial
  4. Add MCP server:
{
  "mcpServers": {
    "vectorclaw": {
      "command": "python3",
      "args": ["-m", "vectorclaw_mcp.server"],
      "env": { "VECTOR_SERIAL": "${VECTOR_SERIAL}" }
    }
  }
}

Tool coverage

Hardware-verified core tools vector_say, vector_drive_off_charger, vector_drive, vector_emergency_stop, vector_head, vector_lift, vector_look, vector_capture_image, vector_face, vector_scan, vector_vision_reset, vector_pose, vector_status, vector_charger_status, vector_touch_status, vector_proximity_status

Experimental tools vector_animate, vector_drive_on_charger, vector_find_faces, vector_list_visible_faces, vector_face_detection, vector_list_visible_objects, vector_cube

Current limitations

  • Charger return (vector_drive_on_charger) is cu...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/danmartinez78/vectorclaw-mcp
Version
—
Commit
ee60e3044921acb4fe352e6762b15ab52a9d4461
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

VectorClaw ClawHub Skill

This folder contains the ClawHub skill definition for VectorClaw.

Files

  • SKILL.md - Main skill definition with metadata and documentation

Publishing

# Login to ClawHub (one-time)
npx clawhub login

# Publish the skill
npx clawhub publish ./skill \
  --slug vectorclaw-mcp \
  --name "VectorClaw MCP" \
  --version 1.0.0 \
  --tags "latest,robotics,vector,mcp"

Testing Locally

Before publishing, test the skill works with your OpenClaw installation by:

  1. Installing the vectorclaw-mcp package
  2. Adding the MCP server config to your mcporter.json
  3. Verifying tools work through OpenClaw

Updates

When updating the skill:

  1. Edit SKILL.md
  2. Increment version in publish command
  3. Add --changelog notes for significant changes

Contenu extrait

SKILL.md
# VectorClaw MCP

VectorClaw connects OpenClaw to an Anki / Digital Dream Labs Vector robot through MCP.
It provides practical robot control primitives for speech, movement, camera capture, and status/sensor reads.

## What you can do

- Speak text with `vector_say`
- Move and position with `vector_drive`, `vector_head`, `vector_lift`
- Capture camera images with `vector_look` and `vector_capture_image`
- Read robot state with `vector_status`, `vector_pose`, `vector_proximity_status`, `vector_touch_status`
- Build look → reason → act workflows

## Vision requirement for look → reason → act

For see → reason → act workflows, the agent must either be vision-capable itself (e.g., a VLM) or have access to a separate vision model/image-interpretation tool to analyze camera images before choosing actions.

## Requirements

- Vector robot configured and reachable
- Wire-Pod running
- SDK configured at `~/.anki_vector/sdk_config.ini`
- `VECTOR_SERIAL` environment variable set

## Quick setup

1. Install package: `pip install vectorclaw-mcp`
2. Configure SDK: `python3 -m anki_vector.configure`
3. Export robot serial: `export VECTOR_SERIAL=your-serial`
4. Add MCP server:

```json
{
  "mcpServers": {
    "vectorclaw": {
      "command": "python3",
      "args": ["-m", "vectorclaw_mcp.server"],
      "env": { "VECTOR_SERIAL": "${VECTOR_SERIAL}" }
    }
  }
}
```

## Tool coverage

**Hardware-verified core tools**
`vector_say`, `vector_drive_off_charger`, `vector_drive`, `vector_emergency_stop`, `vector_head`, `vector_lift`, `vector_look`, `vector_capture_image`, `vector_face`, `vector_scan`, `vector_vision_reset`, `vector_pose`, `vector_status`, `vector_charger_status`, `vector_touch_status`, `vector_proximity_status`

**Experimental tools**
`vector_animate`, `vector_drive_on_charger`, `vector_find_faces`, `vector_list_visible_faces`, `vector_face_detection`, `vector_list_visible_objects`, `vector_cube`

## Current limitations

- Charger return (`vector_drive_on_charger`) is cu...
README
# VectorClaw ClawHub Skill

This folder contains the ClawHub skill definition for VectorClaw.

## Files

- `SKILL.md` - Main skill definition with metadata and documentation

## Publishing

```bash
# Login to ClawHub (one-time)
npx clawhub login

# Publish the skill
npx clawhub publish ./skill \
  --slug vectorclaw-mcp \
  --name "VectorClaw MCP" \
  --version 1.0.0 \
  --tags "latest,robotics,vector,mcp"
```

## Testing Locally

Before publishing, test the skill works with your OpenClaw installation by:

1. Installing the vectorclaw-mcp package
2. Adding the MCP server config to your mcporter.json
3. Verifying tools work through OpenClaw

## Updates

When updating the skill:
1. Edit `SKILL.md`
2. Increment version in publish command
3. Add `--changelog` notes for significant changes

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