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MCP Audio Transcriber

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
-
security - not tested
A
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.

Ein portables, Dockerized-Python-Tool, das das Model Context Protocol für die Audiotranskription mithilfe von Whisper-Modellen implementiert und sowohl CLI- als auch Web-UI-Schnittstellen zum Konvertieren von Audiodateien in JSON-Transkriptionen bietet.

  1. Merkmale
    1. Voraussetzungen
      1. 🔧 Installation
        1. Verwendung
          1. 1. CLI-Transkription
          2. 2. Streamlit-Web-Benutzeroberfläche
          3. 3. Docker
        2. Projektstruktur

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