VibeVoice TTS Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@VibeVoice TTS ServerSpeak the text 'Welcome to the show' using voice alloy."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
VibeVoice TTS Server
Local OpenAI-compatible text-to-speech API server powered by VibeVoice-7B. Generates up to 45 minutes of speech in a single request, with voice cloning from reference audio.
Features
OpenAI-compatible API — drop-in replacement for
POST /v1/audio/speechVoice cloning — upload reference audio to clone any speaker's voice
Long-form generation — natively supports up to ~45 minutes per request (full podcast episodes)
On-demand model loading — loads the 7B model on first request, auto-unloads after idle timeout to free VRAM
Multiple formats — MP3, WAV, OPUS, FLAC, AAC, PCM
MCP server — use as a Claude Code tool for speech synthesis
Platform detection — CUDA > MPS > CPU with optional 4-bit quantization
Related MCP server: Voicevox MCP Server
Quickstart
1. Install
pip install -e .
# With CUDA flash attention:
pip install -e ".[cuda]"
# With 4-bit quantization:
pip install -e ".[quant]"Requires ffmpeg for MP3/OPUS/AAC encoding:
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt install ffmpeg2. Start the server
vibevoice-tts-serverThe model downloads on first request (~14 GB) and loads into VRAM/RAM. Subsequent requests reuse the loaded model.
Options:
vibevoice-tts-server --device cuda --port 8100 --idle-timeout 6003. Generate speech
curl -X POST http://localhost:8101/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{"input": "Hello world, this is VibeVoice!", "voice": "alloy"}' \
--output hello.mp34. Voice cloning with reference audio
Upload a reference audio file to clone a speaker's voice:
curl -X POST http://localhost:8101/v1/audio/speech/upload \
-F "input=Welcome to the show, I'm your host." \
-F "voice=alloy" \
-F "response_format=wav" \
-F "reference_audio=@speaker_sample.wav" \
--output cloned.wav5. Multi-speaker generation (one-shot)
VibeVoice natively generates multi-speaker audio in a single pass. Format the
input with Speaker N: prefixes and upload one reference audio file per speaker:
curl -X POST http://localhost:8101/v1/audio/speech/upload \
-F "input=Speaker 1: Welcome to the show, I'm your host.
Speaker 2: Thanks for having me, great to be here.
Speaker 1: Let's dive right in." \
-F "response_format=wav" \
-F "reference_audio=@host_voice.wav" \
-F "reference_audio=@guest_voice.wav" \
--output podcast.wavOr via the JSON endpoint with file paths:
curl -X POST http://localhost:8101/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{
"input": "Speaker 1: Welcome to the show.\nSpeaker 2: Thanks for having me.",
"instructions": "{\"reference_audio\": [\"/path/to/host.wav\", \"/path/to/guest.wav\"]}"
}' \
--output podcast.mp3Single-speaker voice cloning also works with a single file path:
curl -X POST http://localhost:8101/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{
"input": "Welcome to the show.",
"voice": "alloy",
"instructions": "{\"reference_audio\": \"/path/to/speaker_sample.wav\"}"
}' \
--output cloned.mp3API Reference
POST /v1/audio/speech
JSON body (OpenAI-compatible):
Field | Type | Default | Description |
| string | required | Text to synthesize |
| string |
| Voice preset or speaker name |
| string |
| Model identifier |
| string |
|
|
| float |
| Speed multiplier (0.25 - 4.0) |
| string |
| JSON string with advanced params (see below) |
Instructions JSON fields:
Field | Type | Description |
| string or string[] | Path(s) to reference audio — single path for one speaker, array for multi-speaker |
| float | Classifier-free guidance scale (default: 1.3) |
| int | Diffusion denoising steps (default: 10) |
| int | Audio token limit at 7.5 Hz (0 = unlimited) |
Returns raw audio bytes with the appropriate Content-Type header.
POST /v1/audio/speech/upload
Multipart form — same fields as above, plus:
Field | Type | Description |
| file(s) | One or more audio files for voice cloning — upload multiple for multi-speaker (ordered by Speaker 1, 2, etc.) |
GET /v1/audio/voices
List available voice presets.
GET /v1/models
List available models.
GET /health
Server status, model load state, device info.
Voice Presets
OpenAI Name | VibeVoice Speaker |
alloy | Emma |
echo | Carter |
fable | Davis |
onyx | Mike |
nova | Grace |
shimmer | Frank |
sage | Samuel |
Configuration
All settings can be set via environment variables with the VIBEVOICE_TTS_ prefix:
VIBEVOICE_TTS_HOST=0.0.0.0
VIBEVOICE_TTS_PORT=8101
VIBEVOICE_TTS_MODEL_ID=vibevoice/VibeVoice-7B
VIBEVOICE_TTS_DEVICE=auto # auto, cuda, mps, cpu
VIBEVOICE_TTS_DTYPE=auto # auto, bfloat16, float32
VIBEVOICE_TTS_IDLE_TIMEOUT=300 # seconds before unloading model (0 = never)
VIBEVOICE_TTS_MAX_NEW_TOKENS=0 # 0 = unlimited; tokens are audio frames at 7.5 Hz
VIBEVOICE_TTS_CFG_SCALE=1.3
VIBEVOICE_TTS_N_DIFFUSION_STEPS=10
VIBEVOICE_TTS_QUANTIZE_4BIT=falseMCP Server
Use as a Claude Code tool:
vibevoice-tts-mcpAdd to your Claude Code MCP config:
{
"mcpServers": {
"vibevoice-tts": {
"command": "vibevoice-tts-mcp",
"args": ["--device", "auto"]
}
}
}Tools: synthesize_speech, list_voices, get_tts_status
Running Tests
pip install -e ".[test]"
pytest tests/ -vAudio Token Math
VibeVoice generates audio tokens at 7.5 Hz (7.5 tokens per second of audio). The 7B model has a 32K context window shared between text input tokens and audio output tokens.
Tokens | Duration |
450 | ~1 minute |
4,500 | ~10 minutes |
13,500 | ~30 minutes |
20,250 | ~45 minutes |
By default, max_new_tokens=0 (unlimited), allowing the model to generate until it finishes the input text naturally.
Licensing
This server code is released under the MIT License.
Model license note: Microsoft released VibeVoice-7B under the MIT License. However, Microsoft's model card states the model is "limited to research purpose use" and later removed the TTS code from their official repository citing misuse concerns. Community forks and model weights remain available under MIT. Users should review the model card and applicable terms before deploying in production.
This project is an independent wrapper and is not affiliated with or endorsed by Microsoft.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/tjameswilliams/ai-tts-vibe-openai'
If you have feedback or need assistance with the MCP directory API, please join our Discord server