Skip to main content
Glama
Kokoro TTS MCP Server

Kokoro TTS MCP Server

by giannisanni

Kokoro TTS MCP Server

A Model Context Protocol (MCP) server that provides text-to-speech capabilities using the Kokoro TTS engine. This server exposes TTS functionality through MCP tools, making it easy to integrate speech synthesis into your applications.

Prerequisites

  • Python 3.10 or higher

  • uv package manager

Related MCP server: Typecast API MCP Server

Installation

  1. First, install the uv package manager:

curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Clone this repository and install dependencies:

uv venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate
uv pip install .

Features

  • Text-to-speech synthesis with customizable voices

  • Adjustable speech speed

  • Support for saving audio to files or direct playback

  • Cross-platform audio playback support (Windows, macOS, Linux)

  • Optional OpenAI-compatible remote backend (e.g. kokoro-fastapi) to offload synthesis to a GPU box

Usage

The server provides a single MCP tool generate_speech with the following parameters:

  • text (required): The text to convert to speech

  • voice (optional): Voice to use for synthesis (default: "af_heart")

  • speed (optional): Speech speed multiplier (default: 1.0)

  • save_path (optional): Directory to save audio files

  • play_audio (optional): Whether to play the audio immediately (default: False)

Example Usage

from mcp.client import Client

async with Client() as client:
    await client.connect("kokoro-tts")
    
    # Generate and play speech
    result = await client.call_tool(
        "generate_speech",
        {
            "text": "Hello, world!",
            "voice": "af_heart",
            "speed": 1.0,
            "play_audio": True
        }
    )

Remote backend (OpenAI-compatible)

By default the server runs Kokoro locally. If you already run an OpenAI-compatible TTS endpoint such as kokoro-fastapi (handy for running on a GPU), point the server at it with environment variables — no local torch/kokoro needed:

Variable

Default

Description

KOKORO_BASE_URL

(unset)

OpenAI-compatible base URL, e.g. http://localhost:8880/v1. When set, synthesis is sent here instead of running locally.

KOKORO_API_KEY

not-needed

Bearer token, if your endpoint requires one.

KOKORO_MODEL

kokoro

Model name passed to the endpoint.

Under the hood this calls POST {KOKORO_BASE_URL}/audio/speech with the standard OpenAI payload (model, input, voice, speed, response_format: wav).

Docker

docker build -t kokoro-tts-mcp .
docker run --rm -i kokoro-tts-mcp

To use a remote backend instead of bundling Kokoro:

docker run --rm -i -e KOKORO_BASE_URL=http://host.docker.internal:8880/v1 kokoro-tts-mcp

Dependencies

  • kokoro >= 0.8.4

  • mcp[cli] >= 1.3.0

  • soundfile >= 0.13.1

  • httpx >= 0.27.0

Platform Support

Audio playback is supported on:

  • Windows (using start)

  • macOS (using afplay)

  • Linux (using aplay)

MCP Configuration

Add the following configuration to your MCP settings file:

{
  "mcpServers": {
    "kokoro-tts": {
      "command": "/Users/giannisan/pinokio/bin/miniconda/bin/uv",
      "args": [
        "--directory",
        "/Users/giannisan/Documents/Cline/MCP/kokoro-tts-mcp",
        "run",
        "tts-mcp.py"
      ]
    }
  }
}

License

MIT © Gianni Sanrochman

Available Tools

1 tool
generate_speechD

Inputs: text (required), voice, speed, save_path, +1 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    D1.8/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of confusion. The tool's purpose is clearly distinct.

    Naming Consistency5/5

    The single tool name 'generate_speech' follows a clear verb_noun pattern, which is consistent and descriptive.

    Tool Count3/5

    One tool for a TTS server is borderline; while it may suffice for basic functionality, it feels thin for a typical service that might include voice selection or other parameters.

    Completeness2/5

    A single tool for TTS lacks coverage for common operations like listing voices, configuring parameters, or stopping generation, leading to significant gaps.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

    Related MCP Connectors

    Related MCP Servers