reachy-mini-mcp

Control theReachy Minirobot (or simulator) from Claude, ChatGPT, or any MCP-compatible client.

uv sync --extra reachy-sim uv run python reachy_debug.py

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AI Assistant --stdio--> MCP Server (reachy.py) --> ReachyMini SDK --> Robot / Simulator

The server exposes 16 tools, 4 prompts, and 4 resources via theModel Context Protocol. An AI assistant calls these tools to see through the robot's camera, move the robot, express emotions, play sounds, or detect audio direction -- no robotics knowledge needed on the AI side.

- Python 3.13+
- Reachy Mini robotor the Reachy Mini simulator
- uv(recommended) or pip

git clone https://github.com/ArturSkowronski/reachy-mini-mcp.git cd reachy-mini-mcp uv sync

{ "mcpServers": { "reachy-mini": { "command": "uv", "args": ["--directory", "/path/to/reachy-mini-mcp", "run", "reachy.py"] } } }

Claude Code(.mcp.jsonin your project root):

{ "mcpServers": { "reachy-mini": { "command": "uv", "args": ["--directory", "/path/to/reachy-mini-mcp", "run", "reachy.py"] } } }

To enable thespeak_texttool, set these environment variables:

export ELEVENLABS_API_KEY="your-api-key" export ELEVENLABS_VOICE_ID="your-voice-id" # # Optional override prefix (takes precedence): # export REACHY_ELEVENLABS_API_KEY="your-api-key" # export REACHY_ELEVENLABS_VOICE_ID="your-voice-id"

Default voice (premade/free-tier friendly):Georgewith Voice IDJBFqnCBsd6RMkjVDRZzb.

Favorite voice (author preference):Horatiuswith Voice IDqXpMhyvQqiRxWQs4qSSB.

Optional overrides:ELEVENLABS_MODEL_ID(default:eleven_multilingual_v2),ELEVENLABS_OUTPUT_FORMAT(default:mp3_44100_128).

WAV support: if your ElevenLabs plan allows it, you can setELEVENLABS_OUTPUT_FORMAT=wav_44100to get WAV output instead of MP3.

- Default TTS output is MP3 (mp3_44100_128) because it works on lower ElevenLabs tiers.
- Some Reachy audio backends/environments may not have MP3 decoding available. In that case, MP3 playback can fail even though WAV works.
- If you need ElevenLabs to return WAV directly (wav_44100), ElevenLabs requires a higher tier (minimumPro).
- To force WAV output (when available), override the output format via environment variables:

- REACHY_ELEVENLABS_OUTPUT_FORMAT=wav_44100(preferred, takes precedence)
- orELEVENLABS_OUTPUT_FORMAT=wav_44100

- NO_COLOR: disable ANSI colors inreachy_debug.pyoutput.

- REACHY_DEBUG_ANNOUNCE_PAUSE_S(default:0.6): pause after each announcement before running the step.
- REACHY_DEBUG_TTS_SPEED(default:0.8): ElevenLabs speech speed.

ElevenLabs (used byspeak_textandreachy_debug.pyannouncements):

- REACHY_ELEVENLABS_API_KEYorELEVENLABS_API_KEY(required for TTS): API key.REACHY_prefixed value takes precedence.
- REACHY_ELEVENLABS_VOICE_IDorELEVENLABS_VOICE_ID(optional): voice id. Defaults toJBFqnCBsd6RMkjVDRZzb(George) if not set.
- REACHY_ELEVENLABS_MODEL_IDorELEVENLABS_MODEL_ID(optional): model id (default:eleven_multilingual_v2).
- REACHY_ELEVENLABS_OUTPUT_FORMATorELEVENLABS_OUTPUT_FORMAT(optional): output format (default:mp3_44100_128, optionallywav_44100if your plan allows it).

The server also exposes MCP resources that let AI assistants discover robot capabilities dynamically:

capture_imagegrabs a frame from Reachy Mini's wide-angle HD camera and returns it as inline JPEG content through the MCP protocol. The AI assistant receives the image directly in the conversation -- no file paths, no URLs, no extra setup.

scan_surroundingstakes this further by panning the camera across multiple angles and returning all frames in a single response:

User: "Look around and describe the room" Claude calls scan_surroundings(steps=5, yaw_range=120) <- Robot pans from -60deg to +60deg in 5 steps <- MCP returns 5 labeled JPEG frames + summary text Claude: "Starting from the left I can see a window with blinds, then a whiteboard, your desk with two monitors in the center, a bookshelf to the right, and a door at the far right."

The camera returns a standard BGR numpy frame from OpenCV, which gets JPEG-compressed and delivered as MCPImageContent. Any multimodal AI model that supports image inputs can process it -- Claude, GPT-4o, Gemini, etc.

Every tool carries semantic annotations that tell AI clients how to use it safely:

Pre-built prompt templates that guide AI assistants through common robot interaction scenarios:

express_emotionmaps emoji characters to choreographed movements:

# Install with dev dependencies uv sync --extra dev # Run all tests uv run pytest -v # Unit tests only uv run pytest -v -m "not integration" # Integration tests only (MCP protocol layer) uv run pytest -v -m integration # Lint uv run ruff check . && uv run ruff format --check . # Set up pre-commit hooks pre-commit install

For a one-click, full sequential debug demo (movement, gestures, audio, vision, tracking) with per-step status checks:

uv sync --extra reachy # If you want to auto-spawn the simulator daemon, also install: uv sync --extra reachy-sim uv run python reachy_debug.py

- Announces each upcoming test step (voice via ElevenLabs if configured, otherwise console fallback).
- Executes a full demo suite in sequence.
- Saves all captured images and a markdown run summary toresults/run-YYYYMMDD-HHMMSS/.
- Generates a single report file for the run:run_report.md.

This repo includes a static GitHub Pages site underdocs/(with the dry-run video embedded).

To publish: GitHub repo Settings -> Pages -> "Build and deployment" -> Source: "Deploy from a branch" -> Branch:main-> Folder:/docs.

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