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Kokoro TTS MCP: Lifelike Voices & Ultra-Low Latency - MCP Implementation

Kokoro TTS MCP: Lifelike Voices & Ultra-Low Latency

Empower apps with Kokoro TTS MCP Server – enterprise-grade voice synthesis offering lifelike voices, ultra-low latency, and seamless API integration. Elevate user engagement effortlessly!

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About Kokoro TTS MCP

What is Kokoro TTS MCP: Lifelike Voices & Ultra-Low Latency?

Kokoro TTS MCP is an advanced speech synthesis platform designed to generate high-fidelity audio outputs with minimal latency. It leverages optimized ONNX models to produce natural-sounding voices and integrates seamlessly with cloud storage via AWS S3. The system is ideal for real-time applications requiring both audio quality and rapid response, such as customer service bots, gaming voice systems, and interactive AI assistants.

How to Use Kokoro TTS MCP: Lifelike Voices & Ultra-Low Latency?

Setup Process

  1. Clone the repository and install dependencies using pip install -r requirements.txt
  2. Download the pre-trained models from GitHub and place them in the designated directory
  3. Configure AWS credentials in the .env file for S3 integration

Execution Workflow

Run the server with python main.py then utilize the command-line client to generate audio:

python client.py --text "Sample text" --voice "en_male" --speed 1.0

Kokoro TTS MCP Features

Key Features of Kokoro TTS MCP

  • Real-time Performance: Millisecond-level latency through optimized ONNX runtime execution
  • Multilingual Support: Over 20 language profiles with gender-specific voice variations
  • Cloud Integration: Automatic S3 uploads and lifecycle management via configurable policies
  • Granular Control: Per-request override of S3 storage and voice parameters
  • Self-Healing Architecture: Built-in error handling for model loading and cloud connectivity

Use Cases of Kokoro TTS MCP

Enterprise Applications

Powering IVR systems where 99.9% uptime and sub-200ms response times are critical

Research & Development

Testing voice models in real-world conditions with A/B testing capabilities through voice parameter toggling

Entertainment Industries

Generating dynamic in-game NPC dialogues with emotion modulation options

Accessibility Solutions

Creating custom voice profiles for visually impaired users with adjustable playback speed

Kokoro TTS MCP FAQ

FAQ from Kokoro TTS MCP

Why is latency so low?

Through ONNX model quantization and GPU-accelerated inference pipelines

Can I use my own voice models?

Yes - simply place compatible .onnx files in the /models directory

What happens if S3 fails?

Audio files are retained locally while implementing exponential backoff retries

Does it support WebSocket streaming?

Not natively, but the REST API allows chunked transfers for real-time streaming

How to troubleshoot audio artifacts?

Check the sample_rate parameter alignment between models and device capabilities

Content

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

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

python mcp_client.py --text "Hello, world!"

Reading Text from a File

python mcp_client.py --file my_text.txt

Customizing Voice and Speed

python mcp_client.py --text "Hello, world!" --voice "en_female" --speed 1.2

Disabling S3 Upload

python mcp_client.py --text "Hello, world!" --no-s3

Command-line Options

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

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