Kokoro TTS

by giannisanni

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About

Integrates with the Kokoro TTS engine to provide customizable text-to-speech capabilities, supporting cross-platform audio playback and file output for applications requiring high-quality speech synthesis.

Details

Author
giannisanni
Repository
giannisanni/kokoro-tts-mcp
GitHub stars
5
License
MIT License
Categories
Communication, Other, Design, Developer Tools, File Management, Media, Frontend, Infrastructure

Jump to

- Text-to-speech synthesis with customizable voices
- Adjustable speech speed
- Support for saving audio to files or direct playback
- Cross-platform audio playback support (Windows, macOS, Linux)
- Optional OpenAI-compatible remote backend (e.g. kokoro-fastapi) to offload synthesis to a GPU box

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Kokoro TTS
    Command (node, npx, python, etc.) /Users/giannisan/pinokio/bin/miniconda/bin/uv
    Arguments
    • Argument 1 --directory
    • Argument 2 /Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp
    • Argument 3 run
    • Argument 4 tts-mcp.py

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

The server provides a single MCP tool generate_speech with the following parameters:

- text (required): The text to convert to speech
- voice (optional): Voice to use for synthesis (default: "af_heart")
- speed (optional): Speech speed multiplier (default: 1.0)
- save_path (optional): Directory to save audio files
- play_audio (optional): Whether to play the audio immediately (default: False)

from mcp.client import Client

async with Client() as client:

    await client.connect("kokoro-tts")


Add the following configuration to your MCP settings file:
json
{
"mcpServers": {
"kokoro-tts": {
"command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv",
"args": [
"--directory",
"/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
"run",
"tts-mcp.py"
]
}
}
}
```

generate_speech

Generate speech from text. Parameters: text (required string), voice (optional string), speed (optional float), save_path (optional string), play_audio (optional boolean)

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "kokoro tts": {
            "cwd": "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
            "env": {},
            "args": [
                "--directory",
                "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
                "run",
                "tts-mcp.py"
            ],
            "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv"
        }
    }
}

Linux

{
    "cwd": "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
    "env": [],
    "args": [
        "--directory",
        "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
        "run",
        "tts-mcp.py"
    ],
    "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv"
}

Macos

{
    "cwd": "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
    "env": [],
    "args": [
        "--directory",
        "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
        "run",
        "tts-mcp.py"
    ],
    "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv"
}

Windows

{
    "cwd": "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
    "env": [],
    "args": [
        "--directory",
        "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
        "run",
        "tts-mcp.py"
    ],
    "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv"
}

Kokoro TTS MCP Server

A Model Context Protocol (MCP) server that provides text-to-speech capabilities using the Kokoro TTS engine. This server exposes TTS functionality through MCP tools, making it easy to integrate speech synthesis into your applications.

Prerequisites

- Python 3.10 or higher
- uv package manager

Installation

1. First, install the uv package manager:

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone this repository and install dependencies:

uv venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate
uv pip install .

Features

- Text-to-speech synthesis with customizable voices
- Adjustable speech speed
- Support for saving audio to files or direct playback
- Cross-platform audio playback support (Windows, macOS, Linux)
- Optional OpenAI-compatible remote backend (e.g. kokoro-fastapi) to offload synthesis to a GPU box

Usage

The server provides a single MCP tool generate_speech with the following parameters:

- text (required): The text to convert to speech
- voice (optional): Voice to use for synthesis (default: "af_heart")
- speed (optional): Speech speed multiplier (default: 1.0)
- save_path (optional): Directory to save audio files
- play_audio (optional): Whether to play the audio immediately (default: False)

Example Usage

from mcp.client import Client

async with Client() as client:

    await client.connect("kokoro-tts")

    

    # Generate and play speech

    result = await client.call_tool(

        "generate_speech",

        {

            "text": "Hello, world!",

            "voice": "af_heart",

            "speed": 1.0,

            "play_audio": True

        }

    )

Remote backend (OpenAI-compatible)

By default the server runs Kokoro locally. If you already run an OpenAI-compatible
TTS endpoint such as kokoro-fastapi
(handy for running on a GPU), point the server at it with environment variables —
no local torch/kokoro needed:

| Variable | Default | Description |
|----------|---------|-------------|
| KOKORO_BASE_URL | _(unset)_ | OpenAI-compatible base URL, e.g. http://localhost:8880/v1. When set, synthesis is sent here instead of running locally. |
| KOKORO_API_KEY | not-needed | Bearer token, if your endpoint requires one. |
| KOKORO_MODEL | kokoro | Model name passed to the endpoint. |

Under the hood this calls POST {KOKORO_BASE_URL}/audio/speech with the standard
OpenAI payload (model, input, voice, speed, response_format: wav).

Docker

docker build -t kokoro-tts-mcp .
docker run --rm -i kokoro-tts-mcp

To use a remote backend instead of bundling Kokoro:

docker run --rm -i -e KOKORO_BASE_URL=http://host.docker.internal:8880/v1 kokoro-tts-mcp

Dependencies

- kokoro >= 0.8.4
- mcp[cli] >= 1.3.0
- soundfile >= 0.13.1
- httpx >= 0.27.0

Platform Support

Audio playback is supported on:
- Windows (using start)
- macOS (using afplay)
- Linux (using aplay)

MCP Configuration

Add the following configuration to your MCP settings file:

{
  "mcpServers": {
    "kokoro-tts": {
      "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv",
      "args": [
        "--directory",
        "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
        "run",
        "tts-mcp.py"
      ]
    }
  }
}

License

MIT © Gianni Sanrochman

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Install

Add to Claude Desktop or Cursor

{
    "mcpServers": {
        "kokoro tts": {
            "cwd": "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
            "env": {},
            "args": [
                "--directory",
                "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
                "run",
                "tts-mcp.py"
            ],
            "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv"
        }
    }
}

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