speak_textLABSCO SUMMARY
Speech you hear, not a file you fetch.
The call ends with the audio already playing, and the progress notifications mean the first run — the one that loads the model — does not look like a hang.
What it is
A text-to-speech server built on the Chatterbox TTS model. One tool takes the text, generates the audio, writes it to a temporary file and plays it — with expressiveness and guidance adjustable on each call.
What you get
- Speech generated from text and played automatically, in a single call
- Expressiveness and classifier-free guidance set per call rather than fixed at startup
- The model loaded on first use, with progress reported through loading, generation and playback
- Temporary files cleaned up after playback, with a configurable audio directory when you want to keep them
- Model status and the device in use — MPS, CUDA or CPU — readable from the server
Requirements
Python with the MCP package, torch and torchaudio, plus the Chatterbox TTS module installed separately. Playback uses afplay, so the automatic playback path is macOS-only; hardware acceleration is used when MPS or CUDA is available.
Setup effort
Build from source — git clone https://github.com/digitarald/chatterbox-mcp.git
USE CASES
01
Hearing a draft read back to you
Text goes in and comes out of the speakers, which catches the sentences that do not survive being spoken.
02
Getting an audible signal when something long finishes
A spoken line at the end of a slow task, so you can look away from the screen.
03
Trying a line at different levels of expressiveness
The expressiveness and guidance settings change per call, so two readings can be compared immediately.
04
Working hands-free while something else has your screen
The answer arrives as audio rather than as text you have to switch windows to read.
1 tool
Listed in project docs. Your client may show a different list.
BEFORE YOU INSTALL
What to know first
Tools you get
1 tool named in the project's documentation.
Requires
- Python 3.10+ with pip
- macOS for automatic playback (afplay)
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
You clone this one yourself.
Server setup
TERMINAL
git clone https://github.com/digitarald/chatterbox-mcp.git
cd chatterbox-mcp
pip install mcp torch torchaudio
pip install chatterbox-ttsMCP Clients
Claude Desktop
The path is the absolute path of chatterbox_mcp_server.py in your clone. command has to be the Python you installed the packages into; if Claude Desktop picks up a different one, put that interpreter's absolute path there. Automatic playback uses afplay, which is macOS-only.
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"chatterbox-tts": {
"command": "python",
"args": [
"<YOUR_PATH_TO_CHATTERBOX_MCP>/chatterbox_mcp_server.py"
],
"env": {}
}
}
}
