Fish Audio MCP Server

An MCP (Model Context Protocol) server that provides seamless integration between Fish Audio's Text-to-Speech API and LLMs like Claude, enabling natural language-driven speech synthesis.

What is Fish Audio?

Fish Audio is a cutting-edge Text-to-Speech platform that offers:

• 🌊 State-of-the-art voice synthesis with natural-sounding output
• 🎯 Voice cloning capabilities to create custom voice models
• 🌍 Multilingual support including English, Japanese, Chinese, and more
• ⚡ Low-latency streaming for real-time applications
• 🎨 Fine-grained control over speech prosody and emotions

This MCP server brings Fish Audio's powerful capabilities directly to your LLM workflows.

Features

• 🎙️ High-Quality TTS: Leverage Fish Audio's state-of-the-art TTS models
• 🌊 Streaming Support: Real-time audio streaming for low-latency applications
• 🎨 Multiple Voices: Support for custom voice models via reference IDs
• 🎯 Smart Voice Selection: Select voices by ID, name, or tags
• 📚 Voice Library Management: Configure and manage multiple voice references
• 🔧 Flexible Configuration: Environment variable-based configuration
• 📦 Multiple Audio Formats: Support for MP3, WAV, PCM, and Opus
• 🚀 Easy Integration: Simple setup with any MCP-compatible client

Quick Start

Installation

You can run this MCP server directly using npx:

npx @alanse/fish-audio-mcp-server

Or install it globally:

npm install -g @alanse/fish-audio-mcp-server

Configuration

1. Get your Fish Audio API key from Fish Audio

2. Set up environment variables:

export FISH_API_KEY=your_fish_audio_api_key_here

1. Add to your MCP settings configuration:

Single Voice Mode (Simple)

{
  "mcpServers": {
    "fish-audio": {
      "command": "npx",
      "args": ["-y", "@alanse/fish-audio-mcp-server"],
      "env": {
        "FISH_API_KEY": "your_fish_audio_api_key_here",
        "FISH_MODEL_ID": "speech-1.6",
        "FISH_REFERENCE_ID": "your_voice_reference_id_here",
        "FISH_OUTPUT_FORMAT": "mp3",
        "FISH_STREAMING": "false",
        "FISH_LATENCY": "balanced",
        "FISH_MP3_BITRATE": "128",
        "FISH_AUTO_PLAY": "false",
        "AUDIO_OUTPUT_DIR": "~/.fish-audio-mcp/audio_output"
      }
    }
  }
}

Multiple Voice Mode (Advanced)

{
  "mcpServers": {
    "fish-audio": {
      "command": "npx",
      "args": ["-y", "@alanse/fish-audio-mcp-server"],
      "env": {
        "FISH_API_KEY": "your_fish_audio_api_key_here",
        "FISH_MODEL_ID": "speech-1.6",
        "FISH_REFERENCES": "[{'reference_id':'id1','name':'Alice','tags':['female','english']},{'reference_id':'id2','name':'Bob','tags':['male','japanese']},{'reference_id':'id3','name':'Carol','tags':['female','japanese','anime']}]",
        "FISH_DEFAULT_REFERENCE": "id1",
        "FISH_OUTPUT_FORMAT": "mp3",
        "FISH_STREAMING": "false",
        "FISH_LATENCY": "balanced",
        "FISH_MP3_BITRATE": "128",
        "FISH_AUTO_PLAY": "false",
        "AUDIO_OUTPUT_DIR": "~/.fish-audio-mcp/audio_output"
      }
    }
  }
}

Environment Variables

Variable	Description	Default	Required
FISH_API_KEY	Your Fish Audio API key	-	Yes
FISH_MODEL_ID	TTS model to use (s1, speech-1.5, speech-1.6)	s1	Optional
FISH_REFERENCE_ID	Default voice reference ID (single reference mode)	-	Optional
FISH_REFERENCES	Multiple voice references (see below)	-	Optional
FISH_DEFAULT_REFERENCE	Default reference ID when using multiple references	-	Optional
FISH_OUTPUT_FORMAT	Default audio format (mp3, wav, pcm, opus)	mp3	Optional
FISH_STREAMING	Enable streaming mode (HTTP/WebSocket)	false	Optional
FISH_LATENCY	Latency mode (normal, balanced)	balanced	Optional
FISH_MP3_BITRATE	MP3 bitrate (64, 128, 192)	128	Optional
FISH_AUTO_PLAY	Auto-play audio and enable real-time playback	false	Optional
AUDIO_OUTPUT_DIR	Directory for audio file output	~/.fish-audio-mcp/audio_output	Optional

Configuring Multiple Voice References

You can configure multiple voice references in two ways:

JSON Array Format (Recommended)

Use the FISH_REFERENCES environment variable with a JSON array:

FISH_REFERENCES='[
  {"reference_id":"id1","name":"Alice","tags":["female","english"]},
  {"reference_id":"id2","name":"Bob","tags":["male","japanese"]},
  {"reference_id":"id3","name":"Carol","tags":["female","japanese","anime"]}
]'
FISH_DEFAULT_REFERENCE="id1"

Individual Format (Backward Compatibility)

Use numbered environment variables:

FISH_REFERENCE_1_ID=id1
FISH_REFERENCE_1_NAME=Alice
FISH_REFERENCE_1_TAGS=female,english

FISH_REFERENCE_2_ID=id2
FISH_REFERENCE_2_NAME=Bob
FISH_REFERENCE_2_TAGS=male,japanese

Usage

Once configured, the Fish Audio MCP server provides two tools to LLMs.

Tool 1: fish_audio_tts

Generates speech from text using Fish Audio's TTS API.

Parameters

• text (required): Text to convert to speech (max 10,000 characters)
• reference_id (optional): Voice model reference ID
• reference_name (optional): Select voice by name
• reference_tag (optional): Select voice by tag
• streaming (optional): Enable streaming mode
• format (optional): Output format (mp3, wav, pcm, opus)
• mp3_bitrate (optional): MP3 bitrate (64, 128, 192)
• normalize (optional): Enable text normalization (default: true)
• latency (optional): Latency mode (normal, balanced)
• output_path (optional): Custom output file path
• auto_play (optional): Automatically play the generated audio
• websocket_streaming (optional): Use WebSocket streaming instead of HTTP
• realtime_play (optional): Play audio in real-time during WebSocket streaming

Voice Selection Priority: reference_id > reference_name > reference_tag > default

Tool 2: fish_audio_list_references

Lists all configured voice references.

Parameters

No parameters required.

Returns

• List of configured voice references with their IDs, names, and tags
• Default reference ID

Examples

Basic Text-to-Speech

User: "Generate speech saying 'Hello, world! Welcome to Fish Audio TTS.'"

Claude: I'll generate speech for that text using Fish Audio TTS.

[Uses fish_audio_tts tool with text parameter]

Result: Audio file saved to ./audio_output/tts_2025-01-03T10-30-00.mp3

Using Custom Voice by ID

User: "Generate speech with voice model xyz123 saying 'This is a custom voice test'"

Claude: I'll generate speech using the specified voice model.

[Uses fish_audio_tts tool with text and reference_id parameters]

Result: Audio generated with custom voice model xyz123

Using Voice by Name

User: "Use Alice's voice to say 'Hello from Alice'"

Claude: I'll generate speech using Alice's voice.

[Uses fish_audio_tts tool with reference_name: "Alice"]

Result: Audio generated with Alice's voice

Using Voice by Tag

User: "Generate Japanese speech saying 'こんにちは' with an anime voice"

Claude: I'll generate Japanese speech with an anime-style voice.

[Uses fish_audio_tts tool with reference_tag: "anime"]

Result: Audio generated with anime voice style

List Available Voices

User: "What voices are available?"

Claude: I'll list all configured voice references.

[Uses fish_audio_list_references tool]

Result:
- Alice (id: id1) - Tags: female, english [Default]
- Bob (id: id2) - Tags: male, japanese
- Carol (id: id3) - Tags: female, japanese, anime

HTTP Streaming Mode

User: "Generate a long speech in streaming mode about the benefits of AI"

Claude: I'll generate the speech in streaming mode for faster response.

[Uses fish_audio_tts tool with streaming: true]

Result: Streaming audio saved to ./audio_output/tts_2025-01-03T10-35-00.mp3

WebSocket Real-time Streaming

User: "Stream and play in real-time: 'Welcome to the future of AI'"

Claude: I'll stream the speech via WebSocket and play it in real-time.

[Uses fish_audio_tts tool with websocket_streaming: true, realtime_play: true]

Result: Audio streamed and played in real-time via WebSocket

Development

Local Development

1. Clone the repository:

git clone https://github.com/da-okazaki/mcp-fish-audio-server.git
cd mcp-fish-audio-server

1. Install dependencies:

npm install

1. Create .env file:

cp .env.example .env
# Edit .env with your API key

1. Build the project:

npm run build

1. Run in development mode:

npm run dev

Testing

Run the test suite:

npm test

Project Structure

mcp-fish-audio-server/
├── src/
│   ├── index.ts          # MCP server entry point
│   ├── tools/
│   │   └── tts.ts        # TTS tool implementation
│   ├── services/
│   │   └── fishAudio.ts  # Fish Audio API client
│   ├── types/
│   │   └── index.ts      # TypeScript definitions
│   └── utils/
│       └── config.ts     # Configuration management
├── tests/                # Test files
├── audio_output/         # Default audio output directory
├── package.json
├── tsconfig.json
└── README.md

API Documentation

Fish Audio Service

The service provides two main methods:

1. generateSpeech: Standard TTS generation
2. Returns audio buffer
3. Suitable for short texts

4. Lower memory usage

5. generateSpeechStream: Streaming TTS generation

6. Returns audio stream
7. Suitable for long texts
8. Real-time processing

Error Handling

The server handles various error scenarios:

• INVALID_API_KEY: Invalid or missing API key
• NETWORK_ERROR: Connection issues with Fish Audio API
• INVALID_PARAMS: Invalid request parameters
• QUOTA_EXCEEDED: API rate limit exceeded
• SERVER_ERROR: Fish Audio server errors

Troubleshooting

Common Issues

1. "FISH_API_KEY environment variable is required"
2. Ensure you've set the FISH_API_KEY environment variable

3. Check that the API key is valid

4. "Network error: Unable to reach Fish Audio API"

5. Check your internet connection
6. Verify Fish Audio API is accessible

7. Check for proxy/firewall issues

8. "Text length exceeds maximum limit"

9. Split long texts into smaller chunks

10. Maximum supported length is 10,000 characters

11. Audio files not appearing

12. Check the AUDIO_OUTPUT_DIR path exists
13. Ensure write permissions for the directory

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Fish Audio for providing the excellent TTS API
• Anthropic for creating the Model Context Protocol
• The MCP community for inspiration and examples

Support

For issues, questions, or contributions, please visit the GitHub repository.

Changelog

See CHANGELOG.md for a detailed list of changes.