Install and configure the Talky Talky MCP server for audio capabilities.

1. Clone the repo: git clone https://github.com/shawnrushefsky/talky-talky.git
2. Find the full path to uv: which uv (e.g., /Users/username/.local/bin/uv)
3. Add to my MCP configuration:

   For Claude Desktop (GUI app - MUST use full path to uv):
   {
     "mcpServers": {
       "talky-talky": {
         "command": "/full/path/to/uv",
         "args": ["run", "--directory", "<path-to-talky-talky>", "--extra", "macos-full", "talky-talky"]
       }
     }
   }

   For CLI tools (Claude Code, .mcp.json):
   {
     "mcpServers": {
       "talky-talky": {
         "command": "uv",
         "args": ["run", "--directory", "<path-to-talky-talky>", "--extra", "tts", "--extra", "transcription", "--extra", "analysis", "talky-talky"]
       }
     }
   }

4. Replace paths with actual values
5. Restart the application and verify by checking TTS availability

Platform extras:
- macOS: macos-full (TTS + transcription + analysis, excludes CUDA-only engines)
- Linux with CUDA: linux-cuda-full (all engines including CUDA-only)
- CPU only: cpu-full

Requirements: Python 3.11+, ffmpeg, GPU recommended for TTS/transcription engines.

git clone https://github.com/shawnrushefsky/talky-talky.git
cd talky-talky

# macOS (Apple Silicon or Intel)
pip install -e ".[macos-full]"     # TTS + transcription + analysis

# Linux with NVIDIA CUDA GPU
pip install -e ".[linux-cuda-full]" # All engines including CUDA-only

# CPU only (no GPU)
pip install -e ".[cpu-full]"        # Excludes CUDA-only engines

# TTS engines
pip install -e ".[maya1]"           # Voice design
pip install -e ".[chatterbox]"      # Voice cloning (includes Turbo)
pip install -e ".[xtts]"            # Multilingual cloning
pip install -e ".[kokoro]"          # Pre-built voices
pip install -e ".[seamlessm4t]"     # Multilingual + translation
pip install -e ".[mira]"            # Fast cloning (CUDA only)
pip install -e ".[soprano]"         # Ultra-fast (CUDA only)

# Transcription
pip install -e ".[whisper]"         # OpenAI Whisper
pip install -e ".[faster-whisper]"  # 4x faster Whisper

# Analysis
pip install -e ".[emotion2vec]"     # Emotion detection
pip install -e ".[resemblyzer]"     # Voice similarity
pip install -e ".[nisqa]"           # Speech quality

# Song Generation (CUDA required for LeVo)
pip install -e ".[songgen]"         # LeVo + ACE-Step

# Combined
pip install -e ".[tts]"             # All TTS engines
pip install -e ".[transcription]"   # All transcription engines
pip install -e ".[analysis]"        # All analysis engines

git clone https://github.com/shawnrushefsky/talky-talky.git
cd talky-talky

# Run directly without installing
uv run --extra macos-full talky-talky

# Basic image (audio utilities only)
docker pull ghcr.io/shawnrushefsky/talky-talky:latest
docker run -i ghcr.io/shawnrushefsky/talky-talky:latest

# With GPU access
docker run -i --gpus all talky-talky-cuda

{
  "mcpServers": {
    "talky-talky": {
      "command": "/full/path/to/uv",
      "args": ["run", "--directory", "/path/to/talky-talky", "--extra", "macos-full", "talky-talky"]
    }
  }
}

{
  "mcpServers": {
    "talky-talky": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/talky-talky", "--extra", "tts", "--extra", "transcription", "talky-talky"]
    }
  }
}

speak_maya1(
    text="I can't believe it! <laugh> We did it!",
    output_path="output.wav",
    voice_description="Excited young woman, American accent, energetic"
)

speak_chatterbox(
    text="Hello! [chuckle] Nice to meet you.",
    output_path="output.wav",
    reference_audio_paths=["reference.wav"],
    exaggeration=0.6  # 0.0-1.0+ for expressiveness
)

# Pure TTS
speak_seamlessm4t(
    text="Hello world",
    output_path="hello.wav",
    language="en"
)

# Translate English to French speech
speak_seamlessm4t(
    text="Hello world",
    output_path="bonjour.wav",
    src_language="en",
    language="fr",
    speaker_id=5  # 200 speaker options
)

speak_kokoro(
    text="Welcome!",
    output_path="output.wav",
    voice="af_heart",  # American female
    speed=1.0
)

transcribe_audio(
    audio_path="speech.wav",
    engine="faster_whisper",
    model_size="large-v3",  # tiny, base, small, medium, large-v3
    language="en"  # or None for auto-detection
)

transcribe_with_timestamps(
    audio_path="speech.wav",
    word_level=True  # Get word-level timing
)

verify_tts_output(
    audio_path="generated.wav",
    expected_text="Hello world",
    similarity_threshold=0.8
)

Generate speech saying "Welcome to the future of AI" with a deep male narrator voice using Maya1

Clone the voice from sample.wav using Chatterbox and say "This is voice cloning" with high expressiveness

Transcribe the audio file interview.wav with word-level timestamps

1. Generate intro music search for "podcast intro" sounds
2. Generate speech: "Welcome to Tech Talk" with a professional voice
3. Mix the music and speech together with music at 20% volume
4. Add fade in/out effects

Analyze the speech quality of generated.wav and check if it meets broadcast standards

Use SeamlessM4T to translate "Hello, how are you?" from English to Japanese speech

1. Generate speech with Maya1 saying "Hello there"
2. Create a robot version using the robot voice effect
3. Create a deeper version by shifting formants to 0.8
4. Create a chipmunk version by pitching up 6 semitones

Generate a pop song with LeVo using these lyrics:
[intro-short] ; [verse] Walking through the city lights. Stars are shining bright tonight ;
[chorus] This is our moment. Nothing can stop us now ; [outro-short]

Use description: "female, pop, upbeat, synth"

Generate an instrumental jazz track with ACE-Step:
- Style prompt: "instrumental, jazz, piano, smooth, relaxing"
- Duration: 60 seconds

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Lint and format
ruff check talky_talky
ruff format talky_talky