jackai-stt-mcp
OfficialProvides tools for transcribing audio files using OpenAI's speech-to-text models, supporting file paths, URLs, and base64 input, with options for model selection, language, and prompt.
Click on "Deploy 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., "@jackai-stt-mcp transcribe meeting.mp3 and tell me who said what"
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.
jackai-stt-mcp
Transcribe audio by asking for it in plain language:
You: transcribe ~/Downloads/voice.opus
Claude: تمام تمام، موضوع اللغة العربية إن شاء الله محلول…
An MCP server that runs on your own machine, so the assistant can open the file directly. Nothing to run, no commands to memorise — you mention a file and the assistant does the rest.
No uploading, no copying, no base64. Your OpenAI key never leaves your computer.
Arabic works well, including dialect.
Install
Add this to your MCP client's config. uvx fetches and runs the package on
first use — nothing to install by hand.
{
"servers": {
"jackai-stt": {
"command": "uvx",
"args": ["jackai-stt-mcp"],
"env": {
"OPENAI_API_KEY": "sk-proj-..."
}
}
}
}Where the config lives:
Client | File |
VS Code |
|
Claude Desktop |
|
Claude Code |
|
Cursor |
|
Restart the client, then ask it to transcribe something.
Get an API key at platform.openai.com/api-keys. The account needs credit; transcription runs about $0.0045 per minute.
Related MCP server: transcriber-mcp
Usage
Nothing to run, no syntax to learn. Talk to the assistant the way you normally would and mention the file:
transcribe ~/Downloads/voice.opus
what does the voice note on my desktop say?
read ./recordings/call.m4a and summarise what the client is asking for
transcribe meeting.mp3 and tell me who said what
The assistant recognises that it needs this tool and fills in the arguments from what you said. You never call it yourself or write out its parameters.
That last example needs speaker labels, which only one model produces. Mention it in passing and the assistant picks it:
transcribe meeting.mp3 with the diarize model
Same for a language it keeps mishearing ("it's Egyptian Arabic"), or names it should spell correctly ("the speakers are Ahmad and Sara"). Ordinary words — the table below is just what those words map onto.
What the assistant fills in
You don't set these by hand; this is here so you know what it can control.
Argument | Default | Notes |
| — | Path on this machine. Absolute, relative, or |
| — | Public http(s) URL, downloaded then transcribed. |
| — | For short clips. Prefer |
|
| See the table below. |
| auto-detect | ISO-639-1 ( |
| — | Names or jargon likely in the audio, to steer spelling. |
Exactly one audio source per request.
Models
Model | Cost/min | Speaker labels |
| $0.0045 | no |
| $0.003 | no |
| $0.006 | no |
| $0.006 | yes |
| $0.006 | no |
gpt-transcribe is OpenAI's recommended model: cheaper than whisper-1 and
more accurate. There is no reason to pick whisper-1 unless you need it
specifically.
Formats
flac m4a mp3 mp4 mpeg mpga oga ogg wav webm — up to 25 MB.
.opus files work too. OpenAI rejects that extension even though the bytes are
what it accepts as .ogg, so this server renames it in flight. WhatsApp voice
notes are all .opus, which is exactly the case that would otherwise fail.
Why it runs locally
A remote MCP server cannot read a file you attached in chat. There is no mechanism in the protocol that carries attachments to a server — it has been an open issue since early 2025, and the proposals to add one are still drafts. Base64 through a tool argument works in theory but dies on client argument-size limits after a second or two of audio.
Running on your machine avoids all of it. The server is a process you own, reading a file you own, with a key you hold.
Development
git clone https://github.com/jack-ai-net/stt-mcp
cd stt-mcp
python3 -m venv .venv && .venv/bin/pip install -e ".[dev]"
.venv/bin/python -m pytestTests stub the OpenAI call, so they need no API key and cost nothing.
License
MIT — see LICENSE.
Built by JackAI.
Available Tools
1 tooltranscribe_audioARead-onlyIdempotent
Transcribe ONE audio file and return its text.
Arabic is fully supported: return the Arabic text as transcribed, and do not translate it unless the user asks.
Reads the file directly from this machine, so a path is all that's needed — no uploading, copying, or encoding. Pass exactly one audio source.
Inputs: model, prompt, filename, language, +3 more. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusing it with others. Its purpose is clearly described.
The single tool follows a clear verb_noun pattern (transcribe_audio), which is consistent and predictable.
With only one tool, the server is extremely thin for its apparent scope as an STT service. A typical STT server would include multiple tools for broader coverage.
The server only provides basic single-file transcription, lacking common STT features like remote file handling, language selection, or batch processing. This is a significant gap for a dedicated STT MCP server.
Maintenance
Related MCP Connectors
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Transcribe audio & video to text for AI agents: 100+ languages, speaker labels, webhooks.
Transcribe audio and video and work with your transcript library from any AI app. 119 languages.
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