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io.github.mrfqcentic/mcp-kokoro-tts

Local Kokoro-82M TTS MCP server that synthesizes and plays speech on your machine

Open source Open in the app JSON README (API)

About

Local Kokoro-82M TTS MCP server that synthesizes and plays speech on your machine

Details

Kind
MCP servers
Topic
No topic detected
Publisher
mrfqcentic
Origin
official
Category
ferramentas
Transport
local
Version
0.1.4
Last push
2026-08-22T10:37:01Z
Repository state
ativo
Language
Python
License
NOASSERTION
Added
2026-08-29 04:00:51
Updated
2026-08-29 04:00:51
Origin id
io.github.mrfqcentic/mcp-kokoro-tts

README

# mcp-kokoro-tts

<!-- mcp-name: io.github.mrfqcentic/mcp-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](https://huggingface.co/hexgrad/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:

```json
{
  "mcpServers": {
    "mcp-kokoro-tts": {
      "command": "uvx",
      "args": ["mcp-kokoro-tts"]
    }
  }
}
```

Requires Python 3.12 and [uv](https://docs.astral.sh/uv/). The first server start provisions Kokoro weights and the spaCy English model automatically.

To pre-download both without starting the MCP server:

```bash
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:

1. `TTS_VOICE` env var — voice id or absolute `.pt` path
2. A file in the package `voices/` folder whose name starts with `default`
3. First `.pt` file in `voices/` (alphabetical)
4. The model's bundled `af_heart` voice

```json
{
  "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

1. Bump `version` in `pyproject.toml` (and `server.json` if you are not tagging yet)
2. Commit and tag: `git tag v0.1.2 && git push origin v0.1.2`
3. GitHub Actions runs `publish.yml`:
   - `release` — typecheck, test, build wheel/sdist
   - `pypi-publish` — upload to PyPI with `PYPI_TOKEN`
   - `mcp-registry` — OIDC → MCP Registry (after PyPI succeeds)

## Development

```bash
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](LICENSE) and [NOTICE](NOTICE). Kokoro-82M model weights are downloaded separately under their Apache-2.0 license.

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