kokoro-tts-mcp
MCP server for Kokoro text-to-speech, with adjustable voices/speed and an optional OpenAI-compatible (kokoro-fastapi) backend.
Install / Use
claude mcp add giannisanni -- npx -y github:giannisanni/kokoro-tts-mcpIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
OtherSupported Platforms
Skill content
View source on GitHubKokoro 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
uvpackage manager
Installation
- First, install the
uvpackage 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 speechvoice(optional): Voice to use for synthesis (default: "af_heart")speed(optional): Speech speed multiplier (default: 1.0)save_path(optional): Directory to save audio filesplay_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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