giannisanni/kokoro-tts-mcp

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MCP server for Kokoro text-to-speech, with adjustable voices/speed and an optional OpenAI-compatible (kokoro-fastapi) backend.

概要

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. - Python 3.10 or higher - uv package manager 1. First, install the uv package manager: 2. Clone this repository and install dependencies: - 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 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.

README

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Kokoro TTS MCP Server

Prerequisites

Python 3.10 or higher
uv package manager

Installation

First, install the uv package manager:

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

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

GitHub で README 全文を見る

インストール

docker run --rm -i kokoro-tts-mcp

MCP 初心者？mcpskill.org のガイドから始めましょう →

設定

{
  "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"
      ]
    }
  }
}