transcribe_audioLABSCO SUMMARY
Voice that never leaves the laptop.
Local is the whole proposition: recordings of meetings and voice notes are exactly the material you would rather not upload, and here nothing does. Check the status command before wiring a client up - the tools refuse rather than silently pulling several gigabytes mid-conversation.
What it is
A voice toolkit that runs entirely on your machine, with a small Rust engine underneath - CoreML on Apple Silicon, ONNX elsewhere. The same engine is available as a CLI, as an MCP server, and as agent skills.
What you get
- Transcribe audio locally, across 25 languages, with automatic language detection
- Speak text back, in 9 languages, with a choice of voice
- List the voices and the languages available, so a client can pick before it calls
- Voice-activity detection and diarization as optional downloads
- A single small binary rather than a Python environment - nothing to install for audio decoding
Requirements
Bun 1.3.0 or newer, then install the package globally. Models are a separate, explicit step: the install command reports its sizes first and downloads roughly 2.5 GB on Linux and Windows, or about 0.6 GB on Apple Silicon, which uses a smaller model set. Text to speech needs its own model download. Nothing is fetched behind your back, and the tools fail with an install hint rather than downloading on demand. The client launches the server with the mcp subcommand over stdio.
Setup effort
One command — bun add -g @drakulavich/kesha-voice-kit && kesha install && kesha install --tts && kesha status
USE CASES
Turning a recording into text you can work with
Transcribe the file locally; the language is detected rather than declared, so mixed-language audio still works.
Having the agent read something back
Pick a voice from the list, then synthesise the text to audio without sending it to a provider.
Checking what the machine can actually do
List the supported languages before asking for a transcription or a voice, rather than finding out from an error.
4 tools
Listed in project docs. Your client may show a different list.
synthesize_speechlist_voiceslist_languagesBEFORE YOU INSTALL
What to know first
Tools you get
4 tools named in the project's documentation.
Requires
- Bun >= 1.3.0
- Disk space for the engine and models that kesha install downloads: about 2.5 GB on Linux/Windows, 0.6 GB on Apple Silicon
Where it runs
All 5 documented clients run the server on your machine.
INSTALLATION
Connect your client
Server setup
bun add -g @drakulavich/kesha-voice-kit
kesha install
kesha install --tts
kesha statusMCP Clients
Claude Desktop, Gemini CLI, Cursor
{
"mcpServers": {
"kesha": {
"command": "kesha",
"args": [
"mcp"
]
}
}
}Claude Code
claude mcp add kesha -- kesha mcpCodex
[mcp_servers.kesha]
command = "kesha"
args = ["mcp"]