Skip to main content
Glama
Piper TTS MCP Server

Piper TTS MCP Server

by OnyxFalcon

🎤 Piper TTS MCP Server

A Model Context Protocol (MCP) server that integrates Piper TTS for high-quality text-to-speech functionality. This server provides a speak tool that converts text to speech and plays it directly through your speakers with customizable volume control.

✨ Features

  • 🔊 High-quality text-to-speech using Piper TTS

  • 🎚️ Volume control (0.01 to 1.00)

  • ⚡ Memory-based audio playback (no temporary files)

  • 🔧 Customizable voice parameters (speaker, speed, voice variation)

  • 🚀 Fast and lightweight MCP integration

  • 🔇 Silent operation (no console output)

Related MCP server: Kokoro TTS MCP Server

📋 Requirements

⚠️ Important Prerequisites:

  • Python 3.12+ installed on your system

  • Piper TTS service running on localhost:5000

You can set this up using the included Docker configuration or by running Piper TTS separately.

🚀 Quick Start

1. 🐳 Start Piper TTS Service

Clone this repo and start the TTS service:

git clone https://github.com/CryptoDappDev/piper-tts-mcp.git
cd piper-tts-mcp

Option A: Using Docker Compose (Recommended)

docker compose up -d

Option B: Using Docker Build

docker build -t piper-tts-mcp .
docker run -p 5000:5000 piper-tts-mcp

2. 🔧 Configure MCP Client

Add the server to your MCP configuration (e.g., .mcp.json for Claude Desktop):

{
  "mcpServers": {
    "speak": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/piper-tts-mcp",
        "run",
        "server.py"
      ]
    }
  }
}

3. 🎉 Enjoy!

The speak tool is now available in your MCP client!

🛠️ Usage

The MCP server provides a speak tool with the following parameters:

Parameter

Type

Default

Description

text

string

required

Text to convert to speech

speaker_id

int

0

Voice speaker ID

length_scale

float

1.1

Speech speed (lower = faster)

noise_scale

float

0.667

Voice variation control

noise_w_scale

float

0.333

Pronunciation variation

volume

float

0.15

Volume level (0.01 to 1.00)

Example Usage

# Basic usage
speak("Hello, world!")

# With custom volume
speak("This is louder!", volume=0.5)

# With custom voice settings
speak("Fast and varied speech", 
      length_scale=0.8, 
      volume=0.3, 
      noise_scale=0.8)

🔧 Development

Dependencies

  • Python 3.12+

  • mcp[cli] - MCP framework

  • requests - HTTP client for TTS API

  • pygame - Audio playback

Local Development

# Install dependencies
uv sync

# Run the server
uv run server.py

📦 Docker Configuration

The included Docker setup provides:

  • Piper TTS service on port 5000

  • Pre-configured voice models

  • Automatic startup

🎙️ Voice Models

The default voice model used in this repository is en_GB-cori-high (British English, female voice).

🔍 Exploring Voice Options

🛠️ Changing Voice Models

To use a different voice model:

  1. Choose a voice from the voice samples page

  2. Update the Dockerfile - Replace en_GB-cori-high with your chosen voice model:

    # Download your preferred voice model
    RUN python3 -m piper.download_voices your-chosen-voice-model
    
    # Update the server command
    CMD ["sh", "-c", "python3 -m piper.http_server -m your-chosen-voice-model"]
  3. Rebuild the Docker image:

    docker build -t piper-tts-mcp .
    docker compose up -d

🎨 Creating Custom Voices

Creating your own custom voice requires additional effort and research. Please refer to the Piper documentation for guidance on voice training and customization.

🤝 Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

📄 License

This project is open source and available under the MIT License.

🙏 Acknowledgments


Made with ❤️ for the MCP community

Available Tools

1 tool
speakA
Convert text to speech and play it through the speakers.

Args:
    text: The text to convert to speech
    speaker_id: Voice speaker ID (default: 0)
    length_scale: Speech speed control (default: 1.1, lower = faster)
    noise_scale: Voice variation control (default: 0.667)
    noise_w_scale: Pronunciation variation control (default: 0.333)
    volume: Volume level from 0.01 to 1.00 (default: 0.15)

Returns:
    Success or error message

Inputs: text (required), speaker_id, length_scale, noise_scale, +2 more. Returns: result

Tool Schema Changelog

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

Loading tool schema changelog…

    TDQS

    A3.9/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single 'speak' tool has a clearly defined and distinct purpose of converting text to speech.

    Naming Consistency5/5

    The single tool name 'speak' follows a clear verb-based pattern that directly describes its function. With only one tool, consistency is inherently perfect as there are no other tools to compare against.

    Tool Count2/5

    A single tool feels thin for a TTS server that could reasonably support additional functionality like listing available voices, checking synthesis status, or managing audio output. While the core functionality is present, the tool surface is minimal.

    Completeness2/5

    The server provides basic text-to-speech conversion but lacks complementary tools that would create a complete TTS workflow. There are no tools for voice management, synthesis monitoring, or audio file handling, leaving significant gaps in the domain coverage.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Related MCP Connectors

    Related MCP Servers

    • F
      license
      Not graded
      quality
      D
      maintenance
      Integrates ElevenLabs Text-to-Speech capabilities with Cursor through the Model Context Protocol, allowing users to convert text to speech with selectable voices within the Cursor editor.
      1
      -
    • A
      license
      D
      quality
      D
      maintenance
      Provides text-to-speech capabilities through the Model Context Protocol, allowing applications to easily integrate speech synthesis with customizable voices, adjustable speech speed, and cross-platform audio playback support.
      1
      10
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      A Model Context Protocol server that enables AI models to generate and play high-quality text-to-speech audio through your device's native audio system using Rime's voice synthesis API.
      1
      187 npm
      27
      -
    • F
      license
      Not graded
      quality
      D
      maintenance
      Exposes a text-to-speech announcement tool for the CastleCall home PA system on Raspberry Pi. It enables users to broadcast voice messages using local Piper or cloud-based ElevenLabs providers through the Model Context Protocol.
      -

    Appeared in Searches