Which integrations are available for this server?

Utilizes Ollama as an LLM backend to provide the robot with smart sentiment analysis and AI-generated responses based on the context of coding tasks.

How do I use Reachy Claude MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Reachy Claude MCP Celebrate that I finally fixed that tricky bug!" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Reachy Claude MCP

MCP server that brings Reachy Mini to life as your coding companion in Claude Code.

Reachy reacts to your coding sessions with emotions, speech, and celebratory dances - making coding more interactive and fun!

Features

Feature	Basic	+ LLM	+ Memory
Robot emotions & animations	✅	✅	✅
Text-to-speech (Piper TTS)	✅	✅	✅
Session tracking (SQLite)	✅	✅	✅
Smart sentiment analysis	❌	✅	✅
AI-generated responses	❌	✅	✅
Semantic problem search	❌	❌	✅
Cross-project memory	❌	❌	✅

Requirements

Python 3.10+
Reachy Mini robot or the simulation (see below)
Audio output (speakers/headphones)

Platform Support

Platform	Basic	LLM (MLX)	LLM (Ollama)	Memory
macOS Apple Silicon	✅	✅	✅	✅
macOS Intel	✅	❌	✅	✅
Linux	✅	❌	✅	✅
Windows	⚠️ Experimental	❌	✅	✅

Quick Start

Install the package:
pip install reachy-claude-mcp
Start Reachy Mini simulation (if you don't have the physical robot):
# On macOS with Apple Silicon mjpython -m reachy_mini.daemon.app.main --sim --scene minimal # On other platforms python -m reachy_mini.daemon.app.main --sim --scene minimal
Add to Claude Code (~/.mcp.json):
{ "mcpServers": { "reachy-claude": { "command": "reachy-claude" } } }
Start Claude Code and Reachy will react to your coding!

Installation Options

Basic (robot + TTS only)

pip install reachy-claude-mcp

Without LLM features, Reachy uses keyword matching for sentiment - still works great!

With LLM (Smart Responses)

Option A: MLX (Apple Silicon only - fastest)

pip install "reachy-claude-mcp[llm]"

Option B: Ollama (cross-platform)

# Install Ollama from https://ollama.ai ollama pull qwen2.5:1.5b # Then just use the basic install - Ollama is auto-detected pip install reachy-claude-mcp

The system automatically picks the best available backend: MLX → Ollama → keyword fallback.

Full Features (requires Qdrant)

pip install "reachy-claude-mcp[all]" # Start Qdrant vector database docker compose up -d

Development Install

git clone https://github.com/mchardysam/reachy-claude-mcp.git cd reachy-claude-mcp # Install with all features pip install -e ".[all]" # Or specific features pip install -e ".[llm]" # MLX sentiment analysis (Apple Silicon) pip install -e ".[memory]" # Qdrant vector store

Running Reachy Mini

No Robot? Use the Simulation!

You don't need a physical Reachy Mini to use this. The simulation works great:

# On macOS with Apple Silicon, use mjpython for the MuJoCo GUI mjpython -m reachy_mini.daemon.app.main --sim --scene minimal # On Linux/Windows/Intel Mac python -m reachy_mini.daemon.app.main --sim --scene minimal

The simulation dashboard will be available at http://localhost:8000.

Physical Robot

Follow the Reachy Mini setup guide to connect to your physical robot.

Configuration

Environment Variables

Variable	Default	Description
`REACHY_CLAUDE_HOME`	`~/.reachy-claude`	Data directory for database, memory, voice models
LLM Settings
`REACHY_LLM_MODEL`	`mlx-community/Qwen2.5-1.5B-Instruct-4bit`	MLX model (Apple Silicon)
`REACHY_OLLAMA_HOST`	`http://localhost:11434`	Ollama server URL
`REACHY_OLLAMA_MODEL`	`qwen2.5:1.5b`	Ollama model name
Memory Settings
`REACHY_QDRANT_HOST`	`localhost`	Qdrant server host
`REACHY_QDRANT_PORT`	`6333`	Qdrant server port
Voice Settings
`REACHY_VOICE_MODEL`	(auto-download)	Path to custom Piper voice model

MCP Tools

Basic Interactions

Tool	Description
`robot_respond`	Speak a summary (1-2 sentences) + play emotion
`robot_emotion`	Play emotion animation only
`robot_celebrate`	Success animation + excited speech
`robot_thinking`	Thinking/processing animation
`robot_wake_up`	Start-of-session greeting
`robot_sleep`	End-of-session goodbye
`robot_oops`	Error acknowledgment
`robot_acknowledge`	Quick nod without speaking

Dance Moves

Tool	Description
`robot_dance`	Perform a dance move
`robot_dance_respond`	Dance while speaking
`robot_big_celebration`	Major milestone celebration
`robot_recovered`	After fixing a tricky bug

Smart Features

Tool	Description
`process_response`	Auto-analyze output and react appropriately
`get_project_greeting`	Context-aware greeting based on history
`find_similar_problem`	Search past solutions across projects
`store_solution`	Save problem-solution pairs for future
`link_projects`	Mark relationships between projects

Utilities

Tool	Description
`list_robot_emotions`	List available emotions
`list_robot_dances`	List available dance moves
`get_robot_stats`	Memory statistics across sessions
`list_projects`	All projects Reachy remembers

Available Emotions

amazed, angry, anxious, attentive, bored, calm, celebrate, come, confused, curious, default, disgusted, done, excited, exhausted, frustrated, go_away, grateful, happy, helpful, inquiring, irritated, laugh, lonely, lost, loving, neutral, no, oops, proud, relieved, sad, scared, serene, shy, sleep, success, surprised, thinking, tired, uncertain, understanding, wake_up, welcoming, yes

Available Dances

Celebrations: celebrate, victory, playful, party Acknowledgments: nod, agree, listening, acknowledge Reactions: mind_blown, recovered, fixed_it, whoa Subtle: idle, processing, waiting, thinking_dance Expressive: peek, glance, sharp, funky, smooth, spiral

Usage Examples

Claude can call these tools during coding sessions:

# After completing a task robot_respond(summary="Done! Fixed the type error.", emotion="happy") # When celebrating a win robot_celebrate(message="Tests are passing!") # Big milestone robot_big_celebration(message="All tests passing! Ship it!") # When starting to think robot_thinking() # Session start robot_wake_up(greeting="Good morning! Let's write some code!") # Session end robot_sleep(message="Great session! See you tomorrow.")

Architecture

src/reachy_claude_mcp/ ├── server.py # MCP server with tools ├── config.py # Centralized configuration ├── robot_controller.py # Reachy Mini control ├── tts.py # Piper TTS (cross-platform) ├── memory.py # Session memory manager ├── database.py # SQLite project tracking ├── vector_store.py # Qdrant semantic search ├── llm_backends.py # LLM backend abstraction (MLX, Ollama) └── llm_analyzer.py # Sentiment analysis and summarization

Troubleshooting

Voice model not found

The voice model auto-downloads on first use. If you have issues:

# Manual download mkdir -p ~/.reachy-claude/voices curl -L -o ~/.reachy-claude/voices/en_US-lessac-medium.onnx \ https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx curl -L -o ~/.reachy-claude/voices/en_US-lessac-medium.onnx.json \ https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx.json

No audio on Linux

Install PulseAudio or ALSA utilities:

# Ubuntu/Debian sudo apt install pulseaudio-utils # Fedora sudo dnf install pulseaudio-utils

LLM not working

Check which backend is available:

MLX: Only works on Apple Silicon Macs. Install with pip install "reachy-claude-mcp[llm]"
Ollama: Make sure Ollama is running (ollama serve) and you've pulled a model (ollama pull qwen2.5:1.5b)

If neither is available, the system falls back to keyword-based sentiment detection (still works, just less smart).

Qdrant connection failed

Make sure Qdrant is running:

docker compose up -d

Or point to a remote Qdrant instance:

export REACHY_QDRANT_HOST=your-qdrant-server.com

Simulation won't start

If mjpython isn't found, you may need to install MuJoCo separately or use regular Python:

# Try without mjpython python -m reachy_mini.daemon.app.main --sim --scene minimal

On Linux, you may need to set MUJOCO_GL=egl or MUJOCO_GL=osmesa for headless rendering.

License

MIT

Reachy Claude MCP

Reachy Claude MCP

Features

Requirements

Platform Support

Quick Start

Installation Options

Basic (robot + TTS only)

With LLM (Smart Responses)

Full Features (requires Qdrant)

Development Install

Running Reachy Mini

No Robot? Use the Simulation!

Physical Robot

Configuration

Environment Variables

MCP Tools

Basic Interactions

Dance Moves

Smart Features

Utilities

Available Emotions

Available Dances

Usage Examples

Architecture

Troubleshooting

Voice model not found

No audio on Linux

LLM not working

Qdrant connection failed

Simulation won't start

License

Resources

New MCP Servers

Latest Blog Posts

MCP directory API