mcp-fish-audio-server
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Fish Audio MCP Server is a Model Context Protocol server that integrates Fish Audio's Text-to-Speech API with LLMs like Claude for natural language-driven speech synthesis.
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:
- ๐ State-of-the-art voice synthesis with natural-sounding output
- ๐ฏ Voice cloning capabilities to create custom voice models
- ๐ Multilingual support including English, Japanese, Chinese, and more
- โก Low-latency streaming for real-time applications
- ๐จ Fine-grained control over speech prosody and emotions
This MCP server brings Fish Audio's powerful capabilities directly to your LLM workflows.
Features
- ๐๏ธ High-Quality TTS: Leverage Fish Audio's state-of-the-art TTS models
- ๐ Streaming Support: Real-time audio streaming for low-latency applications
- ๐จ Multiple Voices: Support for custom voice models via reference IDs
- ๐ฏ Smart Voice Selection: Select voices by ID, name, or tags
- ๐ Voice Library Management: Configure and manage multiple voice references
- ๐ง Flexible Configuration: Environment variable-based configuration
- ๐ฆ Multiple Audio Formats: Support for MP3, WAV, PCM, and Opus
- ๐ 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
-
Get your Fish Audio API key from Fish Audio
-
Set up environment variables:
export FISH_API_KEY=your_fish_audio_api_key_here
- 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 IDreference_name
(optional): Select voice by namereference_tag
(optional): Select voice by tagstreaming
(optional): Enable streaming modeformat
(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 pathauto_play
(optional): Automatically play the generated audiowebsocket_streaming
(optional): Use WebSocket streaming instead of HTTPrealtime_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 'ใใใซใกใฏ' 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
- Clone the repository:
git clone https://github.com/da-okazaki/mcp-fish-audio-server.git
cd mcp-fish-audio-server
- Install dependencies:
npm install
- Create
.env
file:
cp .env.example .env
# Edit .env with your API key
- Build the project:
npm run build
- Run in development mode:
npm run dev
Testing
Run the test suite:
npm test
Project Structure
mcp-fish-audio-server/
โโโ src/
โ โโโ index.ts # MCP server entry point
โ โโโ tools/
โ โ โโโ tts.ts # TTS tool implementation
โ โโโ services/
โ โ โโโ fishAudio.ts # Fish Audio API client
โ โโโ types/
โ โ โโโ index.ts # TypeScript definitions
โ โโโ utils/
โ โโโ config.ts # Configuration management
โโโ tests/ # Test files
โโโ audio_output/ # Default audio output directory
โโโ package.json
โโโ tsconfig.json
โโโ README.md
API Documentation
Fish Audio Service
The service provides two main methods:
-
generateSpeech: Standard TTS generation
- Returns audio buffer
- Suitable for short texts
- Lower memory usage
-
generateSpeechStream: Streaming TTS generation
- Returns audio stream
- Suitable for long texts
- 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
-
"FISH_API_KEY environment variable is required"
- Ensure you've set the
FISH_API_KEY
environment variable - Check that the API key is valid
- Ensure you've set the
-
"Network error: Unable to reach Fish Audio API"
- Check your internet connection
- Verify Fish Audio API is accessible
- Check for proxy/firewall issues
-
"Text length exceeds maximum limit"
- Split long texts into smaller chunks
- Maximum supported length is 10,000 characters
-
Audio files not appearing
- Check the
AUDIO_OUTPUT_DIR
path exists - Ensure write permissions for the directory
- Check the
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
License
This project is licensed under the MIT License - see the 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 for a detailed list of changes.