gradio-transcript-mcp: A Gradio MCP Server for Audio/Video Transcription from URLs
@bsmnyk
About gradio-transcript-mcp: A Gradio MCP Server for Audio/Video Transcription from URLs
Gradio demo cum MCP server to generate transcripts from Audio/Video
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"gradio-transcript-mcp": {
"command": "python",
"args": [
"app.py"
]
}
}
}Tools
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Overview
What is gradio-transcript-mcp?
gradio-transcript-mcp is a Gradio application configured as an MCP (Model Control Protocol) server that transcribes audio and video from URLs into text. It uses OpenAI's Whisper and ffmpeg (via yt-dlp) to download, convert, and transcribe multimedia content, enabling MCP clients like Cline to process media inputs efficiently.
How to use gradio-transcript-mcp?
Clone the repository, install dependencies with pip install -r requirements.txt, and run python app.py to start the local Gradio web interface and MCP server. The server exposes a transcribe_url tool, accessible at http://127.0.0.1:7860/gradio_api/mcp/sse. For clients that don't support SSE directly, use mcp-remote as an intermediary. A hosted version is also available at https://bismay-gradio-transcript-mcp.hf.space/gradio_api/mcp/sse.
Key features of gradio-transcript-mcp
- Transcribes audio/video from any URL into English text
- Uses OpenAI's Whisper model via the
transformerslibrary - Converts media to WAV format before transcription
- Dynamic device selection (CPU or GPU)
- Supports local and hosted (Hugging Face Spaces) deployment
- Exposes a single MCP tool:
transcribe_url
Use cases of gradio-transcript-mcp
- Transcribe a podcast, lecture, or meeting from a direct URL
- Integrate multimedia transcription into MCP‑powered workflows (e.g., Cline)
- Convert video content to text for indexing or analysis
- Automate transcription of user‑submitted media links
FAQ from gradio-transcript-mcp
What does gradio-transcript-mcp transcribe?
It transcribes audio and video from a provided URL into English text. It downloads the media, converts it to WAV, and runs Whisper transcription.
What are the runtime dependencies?
Python, gradio[mcp], yt-dlp, transformers, torch, and ffmpeg. The ffmpeg_setup.py script ensures ffmpeg is available.
Where does the transcribed data live?
Transcription happens on the server (local or Hugging Face Spaces). No data is stored permanently; the tool returns the transcription as a string.
How do I connect an MCP client?
Use the SSE URL printed when running the app (e.g., http://127.0.0.1:7860/gradio_api/mcp/sse). Configure your client with that URL. For clients not supporting SSE directly, use npx mcp-remote as an intermediary.
Does it require authentication?
No authentication is mentioned. The server runs locally or on a public Hugging Face Space without built‑in auth.
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