What dependencies are required to run the server?
Python with `uv`, ffmpeg (for .wav to .mp3 conversion), and the Kokoro ONNX model weights. The recommended install method is `uv run`.
@mberg
基本信息
Kokoro Text to Speech (TTS) MCP Server
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"kokoro-tts-mcp": {
"command": "python",
"args": [
"mcp_client.py",
"--text",
"Hello, world!"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Kokoro Tts Mcp is a Model Context Protocol server that converts text to speech using the Kokoro TTS model. It generates .mp3 files that can be stored locally and optionally uploaded to Amazon S3. It is designed for developers who need programmatic TTS generation as part of an AI agent or automation pipeline.
Clone the repository, download the Kokoro ONNX weights (kokoro-v1.0.onnx and voices-v1.0.bin), and install ffmpeg. Add the MCP configuration with required environment variables, then run uv run mcp-tts.py. Use the included client script mcp_client.py with --text or --file to send TTS requests.
Python with `uv`, ffmpeg (for .wav to .mp3 conversion), and the Kokoro ONNX model weights. The recommended install method is `uv run`.
Set the environment variables `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_S3_BUCKET_NAME`, `AWS_S3_REGION`, and `AWS_S3_FOLDER`. Enable S3 with `S3_ENABLED=true`.
Set the `TTS_VOICE` environment variable (default `af_heart`) or use the `--voice` flag when calling `mcp_client.py`.
Locally in the folder specified by `MP3_FOLDER` (default is a `mp3` folder in the script directory). They can also be uploaded to S3 if `S3_ENABLED` is true.
Yes. Pass the `--no-s3` flag to `mcp_client.py` to disable S3 upload for that request. You can also set `S3_ENABLED` to `false` in the environment.
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