Hermes YouTube Transcript MCP Server

Hermes YouTube Transcript MCP Server

Downloads YouTube audio and transcribes it locally using faster-whisper, saving transcripts as Markdown and JSON files for Obsidian and Hermes ingestion.

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README

Hermes YouTube Transcript MCP Server

A Hermes-ready MCP server for STT-first YouTube transcript ingestion. It downloads audio with yt-dlp, normalizes it with ffmpeg, transcribes it with faster-whisper, and saves durable Markdown + JSON outputs suitable for Obsidian and Hermes ingestion.

Exposed tools

  • download_youtube_audio(url_or_video_id)
  • transcribe_audio(file_path)
  • transcribe_youtube(url_or_video_id)
  • save_transcript(transcript, metadata)

Why this stack

  • yt-dlp: reliable YouTube audio fetcher
  • ffmpeg: normalizes audio before transcription
  • faster-whisper: high-quality local STT engine
  • MCP stdio: Hermes can discover and call the tools directly

YouTube captions are not used as the primary transcript source here. They can be added later as a fallback or comparison step, but this server is STT-first by design.

Install

1) System dependencies

Install these first:

  • ffmpeg
  • uv

If you want faster-whisper to use GPU acceleration, install the relevant CUDA/metal stack for your machine. The server defaults to CPU-friendly settings and can be tuned with environment variables.

2) Python dependencies

From this directory:

uv sync

If you prefer a one-off environment install:

uv pip install -e .

Run the MCP server

uv run python -m hermes_youtube_transcript_mcp.server

That starts the server over stdio, which is the best fit for Hermes MCP.

Hermes MCP config

Add this to ~/.hermes/config.yaml:

mcp_servers:
  youtube_transcripts:
    command: "uv"
    args:
      - "run"
      - "--project"
      - "/Users/thomkozik/dev/hermes-youtube-transcript-mcp"
      - "python"
      - "-m"
      - "hermes_youtube_transcript_mcp.server"
    timeout: 300
    connect_timeout: 60

After saving the config, restart Hermes or reload MCP so the tools are rediscovered. In Hermes, the tools should appear with the prefix:

  • mcp_youtube_transcripts_download_youtube_audio
  • mcp_youtube_transcripts_transcribe_audio
  • mcp_youtube_transcripts_transcribe_youtube
  • mcp_youtube_transcripts_save_transcript

You can confirm discovery with:

hermes mcp list
hermes mcp test youtube_transcripts

Environment variables

Optional overrides:

  • HERMES_YT_TRANSCRIPTS_DIR: where Markdown/JSON transcript files are saved
  • HERMES_YT_DOWNLOAD_DIR: where raw downloads are cached
  • HERMES_YT_NORMALIZED_DIR: where normalized WAV files are written
  • HERMES_YT_WHISPER_MODEL: large-v3 by default
  • HERMES_YT_WHISPER_DEVICE: cpu by default
  • HERMES_YT_WHISPER_COMPUTE_TYPE: int8 by default
  • HERMES_YT_WHISPER_BEAM_SIZE: 5 by default

Output format

save_transcript() writes two files:

  1. Markdown with YAML frontmatter and a human-readable transcript body
  2. JSON sidecar with the full metadata and segment list

This format is durable, grep-friendly, and easy to ingest into Obsidian or Thorn.

Verification

Run the unit tests:

uv run python -m unittest discover -s tests -v

If you want a manual smoke test after config is loaded, use Hermes to call mcp_youtube_transcripts_transcribe_youtube on a known public video and check that the Markdown and JSON files are created in the configured output directory.

Notes

  • If ffmpeg is missing, the server raises a clear error before transcription.
  • If yt-dlp or faster-whisper are missing, the server tells you how to install the project dependencies.
  • This implementation intentionally avoids relying on YouTube captions as the primary transcript source.

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