Dash Robot MCP Server
A Model Context Protocol (MCP) server for controlling Wonder Workshop's Dash robot through Claude. This allows Claude to autonomously control Dash's movements, lights, sounds, and head movements, as well as capture photos using a webcam.
Features
Robot Control
- Movement: Move forward, turn left/right, turn around (calibrated for accuracy)
- Sounds: Play 40+ built-in sounds (animals, vehicles, beeps, custom recordings)
- Lights: Control eye brightness and RGB colors for neck and ear LEDs
- Head Movement: Control head yaw (-53° to 53°) and pitch (-5° to 10°)
- Connection Management: Connect, disconnect, and stop the robot
Photo Capture
- Capture photos using a webcam via a separate FastAPI server
- Photos are returned to Claude for visual analysis
Prerequisites
- Python 3.11 or higher
- Wonder Workshop Dash robot
- Bluetooth Low Energy (BLE) support on your computer
- Webcam (optional, for photo capture)
Installation
1. Clone the Repository
git clone https://github.com/jakesimonds/mcpleasework.git
cd mcpleasework
2. Install Dependencies
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install the bleak-dash library (Dash robot BLE control)
pip install git+https://github.com/mewmix/bleak-dash.git
# Install project dependencies
pip install -e .
3. Configure Claude Desktop
Add the following to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"Dash Robot": {
"command": "/path/to/your/venv/bin/uv",
"args": [
"run",
"--with",
"mcp[cli],requests,opencv-python,pillow",
"--with",
"git+https://github.com/mewmix/bleak-dash.git",
"mcp",
"run",
"/path/to/your/mcpleasework/server.py"
]
}
}
}
Replace /path/to/your/ with the actual paths on your system. To find the uv path:
which uv # macOS/Linux
where uv # Windows
4. Start the Photo Server (Optional)
If you want photo capture capabilities:
cd photoServer
pip install fastapi uvicorn opencv-python
uvicorn app:app --port 5001
Keep this running in a separate terminal.
Usage
Testing the Server
Use the MCP development inspector to test the server:
mcp dev server.py
Available Tools
Once configured in Claude Desktop, you can ask Claude to:
connect_to_dash()- Connect to your Dash robotmove_dash_forward(distance)- Move forward (distance in mm, default 1000)dash_turn_left()- Turn 90° leftdash_turn_right()- Turn 90° rightdash_turn_around()- Turn 180°dash_say(sound_name)- Play a sounddash_head_movement(yaw, pitch)- Move the headdash_change_lights(eye_value, neck_color, left_ear_color, right_ear_color)- Change LED colorstake_photo()- Capture a photo (requires photo server)get_available_sounds()- List all available soundsget_sound_descriptions()- Get descriptions of soundsget_movement_limits()- Get parameter limitsget_color_examples()- Get available colorsdisconnect_dash()- Disconnect from the robot
Example Prompts
"Connect to Dash and make him say hello"
"Move Dash forward 500mm, turn right, and change his lights to blue"
"Take a photo and tell me what you see"
"Make Dash do a little dance with sounds and lights"
Project Structure
mcpleasework/
├── server.py # Main MCP server with Dash control tools
├── photoServer/
│ └── app.py # FastAPI server for photo capture
├── photo/ # Directory for captured photos
├── scripts/
│ └── screenshot.py # Webcam utility script
├── pyproject.toml # Project configuration and dependencies
├── requirements.txt # Pinned dependencies
└── README.md # This file
Development
Running Tests
pytest
Code Formatting
This project uses ruff and black for code formatting:
ruff check .
black .
Pre-commit Hooks
Install pre-commit hooks:
pip install pre-commit
pre-commit install
Hardware Notes
Dash Robot Calibration
The turn functions are calibrated for accurate 90° and 180° turns:
dash_turn_left(): 123° at 72 dpsdash_turn_right(): 270° workaround (hardware issue with right turns)dash_turn_around(): 185° at 72 dps
These values may need adjustment based on your floor surface and robot's wheel condition.
BLE Connection
The robot uses Bluetooth Low Energy. Ensure your computer's Bluetooth is enabled and the Dash robot is powered on before attempting to connect.
Troubleshooting
Cannot connect to Dash
- Ensure Bluetooth is enabled
- Turn Dash off and on again
- Make sure no other device is connected to Dash
Photo server not responding
- Check that the photo server is running on port 5001
- Verify your webcam is accessible:
ls /dev/video*(Linux)
Import errors
- Ensure
bleak-dashis installed:pip install git+https://github.com/mewmix/bleak-dash.git - Activate your virtual environment
Credits
This project was originally forked from pamelafox's MCP Python demo template and has been extensively modified for Dash robot control.
- Dash Robot: Wonder Workshop
- bleak-dash Library: mewmix/bleak-dash
- MCP SDK: Anthropic
License
MIT License - see LICENSE file for details











