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VectorClaw

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Enables AI assistants to control Anki Vector robots locally via natural language, providing tools for speech, motion, perception, and interaction without cloud

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Описание

Enables AI assistants to control Anki Vector robots locally via natural language, providing tools for speech, motion, perception, and interaction without cloud dependency.

README

CI Python 3.11+ PyPI License: MIT Status: v1.0.0

Give your AI assistant a body.

VectorClaw is an MCP server that exposes Anki Vector robot capabilities as tools for AI assistants like OpenClaw — bridging natural language to real-world robot actions over a fully local, cloud-free stack.


Architecture

┌─────────────┐    stdio MCP    ┌──────────────────┐    gRPC/WiFi    ┌─────────┐
│  AI Agent   │ ─────────────── │  vectorclaw-mcp  │ ─────────────── │  Vector │
│  (OpenClaw) │                 │  (Python 3.11+)  │                 │  Robot  │
└─────────────┘                 └──────────────────┘                 └─────────┘

All communication is local-only — no cloud dependency at runtime (Wire-Pod setup path).

See Security Architecture for the full trust model.


Table of Contents


Current Status

v1.0.0 Released · 2026-03-01

16 tools verified ✅ on hardware | 7 tools experimental ⚠️

Known limitations:

  • vector_drive_on_charger — activates cube but no reliable charger approach
  • Perception detections — often returns empty lists; SDK semantics under investigation
  • Idle behaviors — Vector's autonomous animations can overlap with commanded behaviors

See ROADMAP.md for the full milestone plan.


Quickstart

Requirements: Python 3.11+ · Wire-Pod running · Vector on local WiFi

For the complete walkthrough (Wire-Pod install, robot auth, WiFi config, troubleshooting) see docs/SETUP.md.

Guided Setup (recommended for new users)

The vectorclaw-setup wizard handles configuration, SDK validation, connectivity check, and a smoke test in one go:

pip install vectorclaw-mcp
vectorclaw-setup

You will be prompted for your robot's serial number and optional IP address. On success you'll see a clear SETUP PASSED message and the next-steps command. On failure every step includes an exact remediation hint.

See docs/OPENCLAW_SETUP_SKILL.md for full details.


Manual Setup

Step 1 — Install VectorClaw

pip install vectorclaw-mcp

Step 2 — Configure Vector SDK

Wire-Pod is the canonical self-hosted server for Vector. Install the SDK distribution and run the one-time auth wizard:

pip install wirepod_vector_sdk
python -m anki_vector.configure

Note: wirepod_vector_sdk installs under the anki_vector Python namespace, so all imports and CLI commands use anki_vector.

Legacy cloud path (best-effort only)

The standalone anki_vector package requires working DDL cloud servers and is brittle on modern Python runtimes.

pip install "vectorclaw-mcp[legacy]"
python -m anki_vector.configure

Prefer wirepod_vector_sdk for reliable, cloud-independent operation.

Step 3 — Set environment variables

export VECTOR_SERIAL="your-robot-serial"   # required — printed on underside of robot
export VECTOR_HOST="192.168.x.x"           # optional — auto-discovered if omitted

Step 4 — Run the server

vectorclaw-mcp
# or
python -m vectorclaw_mcp

MCP Client Configuration

Add the following block to your mcporter.json (or equivalent MCP client config).

With uvx (recommended — no prior install needed)

{
  "mcpServers": {
    "vectorclaw": {
      "command": "uvx",
      "args": ["vectorclaw-mcp"],
      "env": {
        "VECTOR_SERIAL": "your-serial-here"
      }
    }
  }
}

With pip install (if installed locally)

{
  "mcpServers": {
    "vectorclaw": {
      "command": "vectorclaw-mcp",
      "env": {
        "VECTOR_SERIAL": "your-serial-here"
      }
    }
  }
}

Available Tools

Tool Category Description Status
vector_say 🎙️ Speech Make the robot speak text aloud
vector_animate 🎭 Expression Play a named animation ⚠️
vector_drive_off_charger 🏎️ Motion Drive the robot off its charger
vector_drive 🏎️ Motion Drive straight and/or turn in place
vector_drive_on_charger 🏎️ Motion Drive Vector back onto its charger ⚠️
vector_emergency_stop 🏎️ Motion Stop all motion immediately
vector_head 🦾 Actuation Set head angle (−22° – 45°)
vector_lift 🦾 Actuation Set lift height (0.0 – 1.0)
vector_look 👀 Perception Capture image from front camera
vector_capture_image 👀 Perception One-shot image capture
vector_face 🖼️ Display Display custom image on face screen
vector_scan 🔍 Perception Head scan for environment
vector_find_faces 🔍 Perception Scan for faces ⚠️
vector_list_visible_faces 🔍 Perception List currently visible faces ⚠️
vector_face_detection 🔍 Perception Get face detection summary ⚠️
vector_list_visible_objects 🔍 Perception List currently visible objects ⚠️
vector_cube 🎲 Interaction Interact with cube (dock/pickup/drop/roll) ⚠️
vector_vision_reset 👀 Perception Disable all vision modes
vector_pose 📍 Sensing Get current position and orientation
vector_status 📊 Status Get battery level and charging status
vector_charger_status 📊 Status Get charger connection state
vector_touch_status 📊 Status Get touch sensor state
vector_proximity_status 📊 Status Get proximity sensor reading

Status legend: ✅ Verified on hardware | ⚠️ Experimental (limited/reliable issues)

⚠️ Charger prerequisite: vector_drive requires the robot to be off the charger. Call vector_drive_off_charger first, or set VECTOR_AUTO_DRIVE_OFF_CHARGER=1 for automatic undocking.

See docs/MCP_API_REFERENCE.md for full parameter details and response schemas.


Contributing

  1. 🌿 Branch: branch off dev, use <type>/<short-description> naming (e.g. fix/vector-face-payload, feat/vector-scan)
  2. 🧪 Tests: add or update tests under tests/; all tests use the mocked SDK — no hardware required
  3. CI: Python 3.11 is required and must pass; Python 3.12 is experimental/informational — run pytest tests/ -v locally before opening a PR
  4. 🤖 Hardware: if your change touches a tool or connection layer, record a smoke-test run in Hardware Smoke Log following the Hardware Test Playbook
  5. 🎯 PR scope: keep PRs focused — separate docs, feature, and refactor changes to reduce merge-conflict risk with parallel lanes

Docs Map

🛠️ Setup & Runtime

Document Description
Setup Guide Wire-Pod install, robot auth, WiFi, SDK config, troubleshooting
Troubleshooting Common runtime failures, smoke baseline, and escalation path
Runtime Support Supported Python versions and CI policy

📡 API & SDK

Document Description
API Reference MCP tool signatures, parameters, response schemas
Wire-Pod SDK Reference Full SDK capability catalog
Wire-Pod SDK → MCP Integration Priorities Now/Later/Skip decision table for future tools

🔬 Hardware Validation

Document Description
Hardware Test Playbook Repeatable on-robot validation protocol and PR checklist
Hardware Smoke Log Running record of real-world smoke tests
Tool Docking Prerequisites Which tools require undocked state

🔒 Security

Document Description
Security Architecture Threat model, credential handling, input validation, network posture

License

MIT — see LICENSE.

from github.com/danmartinez78/VectorClaw

Установить VectorClaw в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install vectorclaw

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add vectorclaw -- uvx vectorclaw-mcp

FAQ

VectorClaw MCP бесплатный?

Да, VectorClaw MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для VectorClaw?

Нет, VectorClaw работает без API-ключей и переменных окружения.

VectorClaw — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить VectorClaw в Claude Desktop, Claude Code или Cursor?

Открой VectorClaw на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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