kokoro-tts-mcp

<a href="https://glama.ai/mcp/servers/@mberg/kokoro-tts-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@mberg/kokoro-tts-mcp/badge" alt="Kokoro Text to Speech Server MCP server" /> </a> ## Kokoro Text to Speech (TTS) MCP Server Kokoro Text to Speech MCP server that generates .mp3 files with option to upload to S3. Uses: https://huggingface.co/spaces/hexgrad/Kokoro-TTS ## Configuration * Clone to a local repo. * Download the [Kokoro Onnx Weights](https://github.com/thewh1teagle/kokoro-onnx) for [kokoro-v1.0.onnx](https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/kokoro-v1.0.onnx) and [voices-v1.0.bin](https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/voices-v1.0.bin) and store in the same repo. Add the following to your MCP configs. Update with your own values. ``` "kokoro-tts-mcp": { "command": "uv", "args": [ "--directory", "/path/toyourlocal/kokoro-tts-mcp", "run", "mcp-tts.py" ], "env": { "TTS_VOICE": "af_heart", "TTS_SPEED": "1.0", "TTS_LANGUAGE": "en-us", "AWS_ACCESS_KEY_ID": "", "AWS_SECRET_ACCESS_KEY": "", "AWS_REGION": "us-east-1", "AWS_S3_FOLDER": "mp3", "S3_ENABLED": "true", "MP3_FOLDER": "/path/to/mp3" } } ``` ### Install ffmmeg This is needed to convert .wav to .mp3 files For mac: ``` brew install ffmpeg ``` To run locally add these to your .env file. See env.example and copy to .env and modify with your own values. ### Supported Environment Variables - `AWS_ACCESS_KEY_ID`: Your AWS access key ID - `AWS_SECRET_ACCESS_KEY`: Your AWS secret access key - `AWS_S3_BUCKET_NAME`: S3 bucket name - `AWS_S3_REGION`: S3 region (e.g., us-east-1) - `AWS_S3_FOLDER`: Folder path within the S3 bucket - `AWS_S3_ENDPOINT_URL`: Optional custom endpoint URL for S3-compatible storage - `MCP_HOST`: Host to bind the server to (default: 0.0.0.0) - `MCP_PORT`: Port to listen on (default: 9876) - `MCP_CLIENT_HOST`: Hostname for client connections to the server (default: localhost) - `DEBUG`: Enable debug mode (set to "true" or "1") - `S3_ENABLED`: Enable S3 uploads (set to "true" or "1") - `MP3_FOLDER`: Path to store MP3 files (default is 'mp3' folder in script directory) - `MP3_RETENTION_DAYS`: Number of days to keep MP3 files before automatic deletion - `DELETE_LOCAL_AFTER_S3_UPLOAD`: Whether to delete local MP3 files after successful S3 upload (set to "true" or "1") - `TTS_VOICE`: Default voice for the TTS client (default: af_heart) - `TTS_SPEED`: Default speed for the TTS client (default: 1.0) - `TTS_LANGUAGE`: Default language for the TTS client (default: en-us) ## Running the Server Locally Preferred method use UV ``` uv run mcp-tts.py ``` ## Using the TTS Client The `mcp_client.py` script allows you to send TTS requests to the server. It can be used as follows: ### Connection Settings When running the server and client on the same machine: - Server should bind to `0.0.0.0` (all interfaces) or `127.0.0.1` (localhost only) - Client should connect to `localhost` or `127.0.0.1` ### Basic Usage ```bash python mcp_client.py --text "Hello, world!" ``` ### Reading Text from a File ```bash python mcp_client.py --file my_text.txt ``` ### Customizing Voice and Speed ```bash python mcp_client.py --text "Hello, world!" --voice "en_female" --speed 1.2 ``` ### Disabling S3 Upload ```bash python mcp_client.py --text "Hello, world!" --no-s3 ``` ### Command-line Options ```bash python mcp_client.py --help ``` ## MP3 File Management The TTS server generates MP3 files that are stored locally and optionally uploaded to S3. You can configure how these files are managed: ### Local Storage - Set `MP3_FOLDER` in your `.env` file to specify where MP3 files are stored - Files are kept in this folder unless automatically deleted ### Automatic Cleanup - Set `MP3_RETENTION_DAYS=30` (or any number) to automatically delete files older than that number of days - Set `DELETE_LOCAL_AFTER_S3_UPLOAD=true` to delete local files immediately after successful S3 upload ### S3 Integration - Enable/disable S3 uploads with `S3_ENABLED=true` or `DISABLE_S3=true` - Configure AWS credentials and bucket settings in the `.env` file - S3 uploads can be disabled per-request using the client's `--no-s3` option