MCP FishAudio Server
# Fish Audio MCP Server
<div align="center">
<img src="./dcos/icon_fish-audio.webp" alt="Fish Audio Logo" width="300" height="300" />
</div>
[](https://badge.fury.io/js/@alanse%2Ffish-audio-mcp-server) [](https://opensource.org/licenses/MIT)
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](https://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:
```bash
npx @alanse/fish-audio-mcp-server
```
Or install it globally:
```bash
npm install -g @alanse/fish-audio-mcp-server
```
### Configuration
1. Get your Fish Audio API key from [Fish Audio](https://fish.audio/)
2. Set up environment variables:
```bash
export FISH_API_KEY=your_fish_audio_api_key_here
```
3. Add to your MCP settings configuration:
#### Single Voice Mode (Simple)
```json
{
"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)
```json
{
"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:
```bash
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:
```bash
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 '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
1. Clone the repository:
```bash
git clone https://github.com/da-okazaki/mcp-fish-audio-server.git
cd mcp-fish-audio-server
```
2. Install dependencies:
```bash
npm install
```
3. Create `.env` file:
```bash
cp .env.example .env
# Edit .env with your API key
```
4. Build the project:
```bash
npm run build
```
5. Run in development mode:
```bash
npm run dev
```
### Testing
Run the test suite:
```bash
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:
1. **generateSpeech**: Standard TTS generation
- Returns audio buffer
- Suitable for short texts
- Lower memory usage
2. **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
1. **"FISH_API_KEY environment variable is required"**
- Ensure you've set the `FISH_API_KEY` environment variable
- Check that the API key is valid
2. **"Network error: Unable to reach Fish Audio API"**
- Check your internet connection
- Verify Fish Audio API is accessible
- Check for proxy/firewall issues
3. **"Text length exceeds maximum limit"**
- Split long texts into smaller chunks
- Maximum supported length is 10,000 characters
4. **Audio files not appearing**
- Check the `AUDIO_OUTPUT_DIR` path exists
- 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](LICENSE) file for details.
## Acknowledgments
- [Fish Audio](https://fish.audio/) for providing the excellent TTS API
- [Anthropic](https://anthropic.com/) for creating the Model Context Protocol
- The MCP community for inspiration and examples
## Support
For issues, questions, or contributions, please visit the [GitHub repository](https://github.com/da-okazaki/mcp-fish-audio-server).
## Changelog
See [CHANGELOG.md](CHANGELOG.md) for a detailed list of changes.
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one lists voice references (a read-only operation), and the other generates speech (a synthesis operation). There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool.
Both tools follow a consistent snake_case naming pattern with a 'fish_audio_' prefix, followed by a descriptive verb_noun combination (list_references and tts). This uniformity enhances readability and predictability across the tool set.
With only two tools, the server feels under-scoped for a TTS API domain. Key operations like managing references (e.g., create, update, delete) or configuring TTS parameters are missing, limiting the server's utility and forcing agents to work around gaps.
The tool set is severely incomplete for a TTS API. While it covers listing references and generating speech, it lacks essential CRUD operations for references (e.g., create, update, delete) and configuration tools (e.g., set parameters, list voices). This will likely cause agent failures in common workflows.