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

1. Clone the repo

   git clone https://github.com/ShreyasTembhare/MCP---Audio-Transcriber.git
   cd MCP---Audio-Transcriber
   

2. Create a .env

   ASSEMBLYAI_API_KEY=your_assemblyai_api_key_here
   

3. Ensure .gitignore contains:

   .env
   

4. Install Python dependencies

   pip install --upgrade pip
   pip install -r requirements.txt
   

5. 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