Kokoro Text to Speech MCP server that generates .mp3 files with option to upload to S3. Uses: https://huggingface.co/spaces/hexgrad/Kokoro-TTS Clone to a local repo. Download the Kokoro Onnx Weights for kokoro-v1.0.onnx and voices-v1.0.bin and store in the same repo. Add the following to your MCP configs. Update with your own values. This is needed to convert .wav to .mp3 files To run locally add
Add this skill
npx mdskills install mberg/kokoro-tts-mcpWell-documented TTS server with comprehensive setup, S3 integration, and clear configuration examples
Kokoro Text to Speech MCP server that generates .mp3 files with option to upload to S3.
Uses: https://huggingface.co/spaces/hexgrad/Kokoro-TTS
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"
}
}
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.
AWS_ACCESS_KEY_ID: Your AWS access key IDAWS_SECRET_ACCESS_KEY: Your AWS secret access keyAWS_S3_BUCKET_NAME: S3 bucket nameAWS_S3_REGION: S3 region (e.g., us-east-1)AWS_S3_FOLDER: Folder path within the S3 bucketAWS_S3_ENDPOINT_URL: Optional custom endpoint URL for S3-compatible storageMCP_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 deletionDELETE_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)Preferred method use UV
uv run mcp-tts.py
The mcp_client.py script allows you to send TTS requests to the server. It can be used as follows:
When running the server and client on the same machine:
0.0.0.0 (all interfaces) or 127.0.0.1 (localhost only)localhost or 127.0.0.1python mcp_client.py --text "Hello, world!"
python mcp_client.py --file my_text.txt
python mcp_client.py --text "Hello, world!" --voice "en_female" --speed 1.2
python mcp_client.py --text "Hello, world!" --no-s3
python mcp_client.py --help
The TTS server generates MP3 files that are stored locally and optionally uploaded to S3. You can configure how these files are managed:
MP3_FOLDER in your .env file to specify where MP3 files are storedMP3_RETENTION_DAYS=30 (or any number) to automatically delete files older than that number of daysDELETE_LOCAL_AFTER_S3_UPLOAD=true to delete local files immediately after successful S3 uploadS3_ENABLED=true or DISABLE_S3=true.env file--no-s3 optionInstall via CLI
npx mdskills install mberg/kokoro-tts-mcpKokoro Tts MCP is a free, open-source AI agent skill. Kokoro Text to Speech MCP server that generates .mp3 files with option to upload to S3. Uses: https://huggingface.co/spaces/hexgrad/Kokoro-TTS Clone to a local repo. Download the Kokoro Onnx Weights for kokoro-v1.0.onnx and voices-v1.0.bin and store in the same repo. Add the following to your MCP configs. Update with your own values. This is needed to convert .wav to .mp3 files To run locally add
Install Kokoro Tts MCP with a single command:
npx mdskills install mberg/kokoro-tts-mcpThis downloads the skill files into your project and your AI agent picks them up automatically.
Kokoro Tts MCP works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Gemini Cli, Amp, Roo Code, Goose. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.