About mcp-kokoro-tts
mcp-kokoro-tts is a local text-to-speech MCP server built on Kokoro-82M. It is for MCP client users who want to hear an agent's text output, with synthesis running on the machine and no API key required.
Key features
- 01Synthesize and play speech locally
- 02Configure voice and playback speed
- 03List available voices and the default
- 04Provision model weights and spaCy English model
Use cases
- 01Listen to an agent read text aloud
- 02Choose a voice and adjust playback speed
- 03Synthesize speech locally without an API key
MCP support
The server provides the speak and list_voices tools to MCP clients. When a client calls speak, it synthesizes speech locally, writes a WAV file, and plays it.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEmcp-kokoro-tts
Local Kokoro-82M text-to-speech MCP server. When your agent calls speak, it synthesizes speech and plays it on your machine so you can hear the harness talk.
Works with any MCP client: Claude Desktop, Claude Code, Cursor, VS Code, opencode, Cline, and more. One short config block, no API keys — synthesis runs locally with Kokoro-82M.
On first start, the server provisions two things that are not on PyPI: the Kokoro-82M weights (~312 MB) into a local cache, and spaCy's English model (en_core_web_sm) into the same Python environment the server is running in. That second install is required because Kokoro's G2P pipeline loads spaCy, and a uvx / uv tool environment will not have the model unless this package puts it there.
Install
Add to your client's MCP config:
{
"mcpServers": {
"mcp-kokoro-tts": {
"command": "uvx",
"args": ["mcp-kokoro-tts"]
}
}
}
Requires Python 3.12 and uv. The first server start provisions Kokoro weights and the spaCy English model automatically.
To pre-download both without starting the MCP server:
uvx mcp-kokoro-tts-provision
Make the agent call it
Add one line to your AGENTS.md / CLAUDE.md / system prompt:
When the user wants to hear something spoken aloud, call the `speak` tool with clear, natural text.
Tools
speak
Synthesizes speech, writes a WAV file, and plays it locally.
| Param | Required | Description |
|---|---|---|
text | yes | Text to speak (max 500 chars) |
voice | no | Voice id (e.g. af_heart) or absolute path to a .pt voice file |
speed | no | Playback speed multiplier (default 1.0) |
list_voices
Lists available Kokoro voices and the currently selected default.
Choosing your voice
Resolution order:
TTS_VOICEenv var — voice id or absolute.ptpath- A file in the package
voices/folder whose name starts withdefault - First
.ptfile invoices/(alphabetical) - The model's bundled
af_heartvoice
{
"mcpServers": {
"mcp-kokoro-tts": {
"command": "uvx",
"args": ["mcp-kokoro-tts"],
"env": {
"TTS_VOICE": "af_heart"
}
}
}
}
Environment variables
| Variable | Description |
|---|---|
TTS_VOICE | Default voice id or absolute .pt path |
TTS_MODEL_DIR | Override model cache directory |
TTS_HF_CACHE_DIR | Override Hugging Face hub cache directory |
TTS_OUTPUT_DIR | Directory for generated WAV files |
TTS_PLAY | Set to 0 to synthesize without local playback |
HF_TOKEN | Optional Hugging Face token for faster downloads |
Platforms
| OS | Synthesis | Playback |
|---|---|---|
| macOS | yes | afplay |
| Linux | yes | ffplay, paplay, or aplay |
| Windows | yes | PowerShell MediaPlayer |
espeak-ng is optional. English works without it; install it for better out-of-vocabulary coverage and some non-English languages.
Publishing
Tagging a version runs GitHub Actions publish.yml, which uploads to PyPI then the MCP Registry.
Publishing to PyPI uses the repo secret PYPI_TOKEN (a PyPI API token). GitHub trusted publishing can also be configured on the PyPI project; this workflow authenticates with the token so a first release does not depend on pending-publisher matching.
Release
- Bump
versioninpyproject.toml(andserver.jsonif you are not tagging yet) - Commit and tag:
git tag v0.1.2 && git push origin v0.1.2 - GitHub Actions runs
publish.yml:release— typecheck, test, build wheel/sdistpypi-publish— upload to PyPI withPYPI_TOKENmcp-registry— OIDC → MCP Registry (after PyPI succeeds)
Development
cd mcps-tts
python3.12 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pyright
pytest
python -m mcp_kokoro_tts
License
Apache-2.0. See LICENSE and NOTICE. Kokoro-82M model weights are downloaded separately under their Apache-2.0 license.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.