MCP Audio Transcriber

A Dockerized Python tool that implements the Model Context Protocol (MCP) via AssemblyAI's API. Upload or point to an audio file, and receive a structured JSON transcription.

Features

AssemblyMCP: a concrete MCP implementation that uses AssemblyAI's REST API
Command-line interface (app.py):
python app.py <input_audio> <output_json>
Streamlit web UI (streamlit_app.py):
- Upload local files or paste URLs
- Click Transcribe
- Preview transcript and download JSON
Docker support for environment consistency and portability

Prerequisites

Python 3.10+
An AssemblyAI API key
ffmpeg (for local decoding, if using local files)
(Optional) Docker Desktop / Engine
(Optional) Streamlit (pip install streamlit)

🔧 Installation

Clone the repo
git clone https://github.com/ShreyasTembhare/MCP---Audio-Transcriber.git cd MCP---Audio-Transcriber
Create a .env
ASSEMBLYAI_API_KEY=your_assemblyai_api_key_here
Ensure .gitignore contains:
.env
Install Python dependencies
pip install --upgrade pip pip install -r requirements.txt
Install ffmpeg
- Ubuntu/Debian: sudo apt update && sudo apt install ffmpeg -y
- Windows: download from https://ffmpeg.org and add its bin/ to your PATH

Usage

1. CLI Transcription

python app.py <input_audio> <output_json>

<input_audio>: any file or URL supported by AssemblyAI
<output_json>: path for the generated JSON

Example:

python app.py data/input.ogg data/output.json
cat data/output.json

2. Streamlit Web UI

streamlit run streamlit_app.py

Open http://localhost:8501
Upload or enter an audio URL
Click Transcribe
Download the JSON result

3. Docker

Build the image:

docker build -t mcp-transcriber .

Run it (mounting your data/ folder):

docker run --rm \
  -e ASSEMBLYAI_API_KEY="$ASSEMBLYAI_API_KEY" \
  -v "$(pwd)/data:/data" \
  mcp-transcriber:latest \
  /data/input.ogg /data/output.json

Then inspect:

ls data/output.json
cat data/output.json

Windows PowerShell:

docker run --rm `
  -e ASSEMBLYAI_API_KEY=$env:ASSEMBLYAI_API_KEY `
  -v "${PWD}\data:/data" `
  mcp-transcriber:latest `
  /data/input.ogg /data/output.json

Project Structure

MCP-Audio-Transcriber/
├── app.py               # CLI entrypoint (AssemblyMCP only)
├── mcp.py               # ModelContextProtocol + AssemblyMCP
├── streamlit_app.py     # Streamlit interface
├── requirements.txt     # assemblyai, python-dotenv, streamlit, etc.
├── Dockerfile           # builds the container
├── .gitignore           # ignores .env, __pycache__, etc.
├── LICENSE              # MIT license
└── data/                # sample input and output
    ├── input.ogg
    └── output.json

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

A portable, Dockerized Python tool that implements Model Context Protocol for audio transcription using Whisper models, featuring both CLI and web UI interfaces for converting audio files to JSON transcriptions.

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