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Kokoro Tts MCP

by mberg

Generates local MP3 speech from Kokoro ONNX models, with optional S3 upload and configurable file cleanup.

Install Kokoro Tts MCP

Pick your client, then add it in one click or paste the config.

No confirmed install command yet

We only publish a config when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for mberg/kokoro-tts-mcp, and we’d rather show nothing than a guess you’d paste into your client.

Open setup steps on GitHub

Overview

mberg/kokoro-tts-mcp MCP server converts text into MP3 audio using local Kokoro ONNX weights. It stores generated files in a configured local folder and can upload them to S3-compatible storage. Voice, speed, language, retention, and upload behavior are controlled through environment variables or client options. Reach for mberg/kokoro-tts-mcp MCP server when speech generation should run locally without a hosted TTS API.

Use cases

  • Generate MP3 narration from text
  • Convert text files into speech audio
  • Store generated audio in an S3 bucket
  • Clean up old local MP3 files

Key features

  • Local Kokoro ONNX text-to-speech
  • MP3 output through FFmpeg
  • Configurable voice, speed, and language
  • Optional S3-compatible uploads
  • Retention and post-upload file cleanup

Security & health

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Adoption & maintenance

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GitHub stars83Stargazers on the source repository.
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Directory activity5 viewsConfig copies, upvotes, and views on AllMCPs.

How Kokoro Tts MCP works

What mberg/kokoro-tts-mcp MCP server does

Audio is generated locally from the Kokoro ONNX model and voice data, rather than being sent to a hosted speech API. The resulting files are written to a local MP3 directory and may also be uploaded to an S3 bucket.

The default synthesis settings include the af_heart voice, speed 1.0, and the en-us language. These defaults can be changed through environment variables. The accompanying client can submit text directly, read text from a file, select a voice, change playback speed, or disable S3 upload for an individual request.

How it works

The repository must contain two Kokoro model files: kokoro-v1.0.onnx and voices-v1.0.bin. The server loads these local assets to produce speech. FFmpeg is also needed to convert the generated WAV audio into MP3 format; on macOS, the documented installation command is brew install ffmpeg.

A local process can be started with uv run mcp-tts.py. The MCP configuration shown by the project runs that script through uv from the cloned repository directory. The server can bind to all interfaces or localhost, with a default port of 9876 for the network configuration described in the README.

When S3 support is enabled, the server uses configured AWS credentials, bucket settings, region, folder, and optional endpoint URL. S3-compatible services can therefore be configured through an alternate endpoint. Local files can remain in the MP3 directory, be removed after a successful upload, or be cleaned up after a configured retention period.

Setup and configuration

Clone the repository, download the referenced Kokoro ONNX weights, and place both model files in the repository. Install FFmpeg separately before starting the server. Copy the example environment file to .env, then set values appropriate for local storage and, if needed, S3.

Important settings include MP3_FOLDER for local output, TTS_VOICE, TTS_SPEED, and TTS_LANGUAGE for synthesis defaults, and S3_ENABLED for upload behavior. S3 configuration uses access credentials, a bucket name, a region, and an optional folder or custom endpoint. MP3_RETENTION_DAYS controls age-based deletion, while DELETE_LOCAL_AFTER_S3_UPLOAD controls removal after a successful transfer.

Tools and capabilities

mberg/kokoro-tts-mcp MCP server supports these documented workflows:

  • Generate an MP3 from text.
  • Read source text from a file through the supplied client.
  • Override the voice and speed for a request.
  • Upload generated audio to S3 when enabled.
  • Disable S3 upload for a specific client request.
  • Keep local files, remove them after upload, or delete older files automatically.

Limitations and notes

The material does not list the MCP tool names or provide a hosted endpoint. Operation depends on locally downloaded model files and an FFmpeg installation. S3 uploads require the relevant AWS or S3-compatible configuration, but the documented client can bypass S3 for a request. The README presents local execution and configuration examples rather than a packaged registry installation command.

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Frequently Asked Questions about Kokoro Tts MCP

Clone the repository, download `kokoro-v1.0.onnx` and `voices-v1.0.bin` into it, install FFmpeg, and run `uv run mcp-tts.py`.

The README provides a generic MCP configuration with a `uv` command but does not name Claude Desktop or confirm client-specific compatibility.

Set S3 upload and bucket configuration in the environment, including credentials, bucket name, region, and optional folder or endpoint settings.

Use the supplied client with the `--no-s3` option.

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