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MCP Coqui TTS Server

A Model Context Protocol (MCP) server that provides text-to-speech synthesis capabilities using Coqui TTS, including voice cloning support.

Features

  • Text-to-Speech Synthesis: Convert text to natural-sounding speech

  • Multiple Models: Support for various TTS models and languages

  • Voice Cloning: Clone voices from audio samples using XTTS models

  • Long Text Support: Automatic chunking for longer texts

  • Customizable Output: Control speed, speaker, and language settings

Related MCP server: Kokoro MCP Server

Prerequisites

Before using this MCP server, you need to install Coqui TTS:

pip install TTS

For voice cloning and concatenation features, you'll also need ffmpeg:

# macOS
brew install ffmpeg

# Ubuntu/Debian
sudo apt-get install ffmpeg

# Windows (using chocolatey)
choco install ffmpeg

Installation

From npm

npm install -g @s.lfr/mcp-coqui-tts

From Source

git clone https://github.com/yourusername/mcp-coqui-tts.git
cd mcp-coqui-tts
npm install
npm link

Usage

With Claude Desktop

Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "coqui-tts": {
      "command": "npx",
      "args": ["@s.lfr/mcp-coqui-tts"]
    }
  }
}

Or if installed from source:

{
  "mcpServers": {
    "coqui-tts": {
      "command": "node",
      "args": ["/path/to/mcp-coqui-tts/index.js"]
    }
  }
}

Available Tools

1. speak

Convert text to speech with customizable parameters.

Parameters:

  • text (required): The text to convert to speech

  • model: TTS model to use (default: "tts_models/en/ljspeech/tacotron2-DDC")

  • output_path: Where to save the audio file

  • speaker_idx: Speaker index for multi-speaker models

  • language_idx: Language index for multi-language models

  • speed: Speed factor (1.0 is normal speed)

Example:

{
  "text": "Hello, this is a test of the text to speech system.",
  "model": "tts_models/en/ljspeech/tacotron2-DDC",
  "output_path": "/tmp/output.wav",
  "speed": 1.2
}

2. list_models

List all available TTS models.

Parameters: None

3. synthesize_long_text

Synthesize longer texts with automatic chunking and concatenation.

Parameters:

  • text (required): The long text to convert

  • model: TTS model to use

  • output_path: Where to save the final audio

  • chunk_size: Maximum characters per chunk (default: 500)

Example:

{
  "text": "This is a very long text that will be automatically split into chunks...",
  "output_path": "/tmp/long_speech.wav",
  "chunk_size": 500
}

4. clone_voice

Clone a voice from an audio sample (requires XTTS model).

Parameters:

  • text (required): Text to speak in the cloned voice

  • reference_audio (required): Path to reference audio for voice cloning

  • output_path: Where to save the output

  • language: Language code (default: "en")

Example:

{
  "text": "This will be spoken in the cloned voice.",
  "reference_audio": "/path/to/sample.wav",
  "output_path": "/tmp/cloned_voice.wav",
  "language": "en"
}

English Models

  • tts_models/en/ljspeech/tacotron2-DDC - High quality English TTS

  • tts_models/en/ljspeech/fast_pitch - Fast English TTS

  • tts_models/en/vctk/vits - Multi-speaker English (110 speakers)

Multilingual Models

  • tts_models/multilingual/multi-dataset/xtts_v2 - Supports voice cloning

  • tts_models/multilingual/multi-dataset/your_tts - Multilingual with voice cloning

Other Languages

Run list_models to see all available models for different languages.

Deployment on Smithery

To deploy this MCP server on Smithery:

  1. Fork this repository

  2. Connect your GitHub account to Smithery

  3. Create a new MCP server on Smithery

  4. Select this repository

  5. Deploy

The server will be automatically available for use with any MCP-compatible client.

Development

Running Locally

npm start

Testing

You can test the server using the MCP inspector:

npx @modelcontextprotocol/inspector node index.js

Troubleshooting

Common Issues

  1. "tts: command not found"

    • Make sure Coqui TTS is installed: pip install TTS

    • Ensure Python/pip binaries are in your PATH

  2. "ffmpeg: command not found"

    • Install ffmpeg for your operating system (see Prerequisites)

  3. Model download fails

    • First run may take time as models are downloaded

    • Check internet connection

    • Ensure sufficient disk space (~1-5GB per model)

  4. Voice cloning not working

    • Requires XTTS v2 model

    • Reference audio should be clear, 5-10 seconds long

    • WAV format recommended for reference audio

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT

Acknowledgments

Support

For issues and questions, please open an issue on GitHub.

Available Tools

4 tools
clone_voiceB

Clone a voice from an audio sample (requires XTTS model)

Inputs: text (required), reference_audio (required), language, output_path.

list_modelsA

List available TTS models

Inputs: no named parameters.

speakC

Convert text to speech using Coqui TTS

Inputs: text (required), model, speed, output_path, +2 more.

synthesize_long_textB

Synthesize longer text with automatic chunking

Inputs: text (required), model, chunk_size, output_path.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.5/5.0

    Scored across 4 tools

    Disambiguation4/5

    speak and synthesize_long_text both perform text-to-speech, but synthesize_long_text is explicitly for longer text with automatic chunking, which sets it apart. clone_voice and list_models are clearly distinct, so overall only minor overlap exists.

    Naming Consistency4/5

    Most tools use a verb_noun pattern (list_models, synthesize_long_text, clone_voice), but 'speak' is a bare verb without an object, creating a slight inconsistency. The pattern is still mostly predictable away from this.

    Tool Count5/5

    With four tools, the server is well-scoped for its TTS purpose: listing models, synthesizing short and long text, and cloning voices. Each tool earns its place, and the count feels neither too thin nor too heavy.

    Completeness4/5

    The tool surface covers the core TTS workflows: model discovery, standard and long-form synthesis, and voice cloning. Minor gaps like audio streaming or detailed model management are not essential for a basic TTS server, so the coverage is solid.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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