Other MCP Server · MODEL CONTEXT PROTOCOL
giannisanni kokoro tts mcp
giannisanni kokoro tts mcp is a community-listed Model Context Protocol server. Review the source repository before installation.
连接能力
giannisanni kokoro tts mcp 为 AI Agent 提供什么
- 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)
- `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)
- kokoro >= 0.8.4
- mcp[cli] >= 1.3.0
- soundfile >= 0.13.1
- Windows (using `start`)
- macOS (using `afplay`)
- Linux (using `aplay`)
安全
MCP 收录不等于安全审核
MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。
README
仓库文档
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
uvpackage manager
- 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 .- 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 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)
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
}
)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 build -t kokoro-tts-mcp .
docker run --rm -i kokoro-tts-mcpTo 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- kokoro >= 0.8.4
- mcp[cli] >= 1.3.0
- soundfile >= 0.13.1
- httpx >= 0.27.0
Audio playback is supported on:
- Windows (using
start) - macOS (using
afplay) - Linux (using
aplay)
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"
]
}
}
}MIT © Gianni Sanrochman
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