youtube-digest

MCP server that turns YouTube videos into text. You give it a URL, Gemini watches the video (audio and visuals) through its documented YouTube-URL input, and you get the full content as text plus a short summary. Results are stored in SQLite, indexed by video id, so digesting the same URL twice returns the stored version and costs nothing extra.

There is no downloading and no caption scraping involved. Passing a public YouTube URL as multimodal input is a documented feature of the Gemini API (video understanding).

Built for ZCode / Z.AI, works with any MCP client that speaks stdio (Claude Code, Cursor, etc.).

Tools

The full text stays in the video's original language; the short summary comes in Spanish. In practice you say "digiere this video" to your assistant and it calls digest, then processes or presents the text however you asked.

Related MCP server: yt-analysis-mcp

Setup

git clone <repo> && cd youtube-digest-videos-mcp
python3 -m venv .venv
.venv/bin/pip install -r requirements.txt
cp .env.example .env   # then put your GEMINI_API_KEY in it

Get a key at aistudio.google.com/apikey. The key lives only in .env, which is gitignored. Never commit it.

Smoke test without an MCP client:

.venv/bin/python cli.py "https://www.youtube.com/watch?v=jNQXAC9IVRw"
.venv/bin/python cli.py --list
.venv/bin/python cli.py --search "some words"

Registering in ZCode

Add to the mcp.servers object in ~/.zcode/cli/config.json:

"youtube-digest": {
  "command": "/absolute/path/to/youtube-digest-videos-mcp/.venv/bin/python",
  "args": ["/absolute/path/to/youtube-digest-videos-mcp/server.py"]
}

Where the data lives

• data/digests.db - SQLite database (WAL mode). One row per video: text, summary, key points, topics, language, model used, fetch counter.

• data/digests/<video_id>.md - a readable Markdown mirror of each digest.

Both are gitignored. The digests reproduce third-party video content, so they belong on your machine only; see docs/reporte_2026-09-29_riesgos-publicacion-github.md before publishing anything from this repo.

Models

The server tries a chain of models and uses the first one that responds: gemini-3.5-flash, then gemini-3-flash-preview, then gemini-flash-lite-latest. The chain skips models that are gone (404) or saturated (503) and retries once after 20 seconds when everything is busy. As of September 2026 the gemini-2.5-* family returns 404 for new keys.

Override with GEMINI_MODEL (single model) or GEMINI_MODELS (comma-separated chain) in .env. The model that produced each digest is recorded in its row.

Limits and costs

• Only public videos. Private, unlisted-restricted or deleted videos are rejected via a free oEmbed check before any Gemini call is spent.

• Gemini bills per video second (roughly 300 tokens per second of media). Long videos cost more; a 90-minute video can also hit output limits and produce a truncated text.

• Free-tier keys have per-day video limits; paid keys are billed per token.

• An exposed key is a billable key. Turn on budget alerts in AI Studio and keep .env out of git (GitHub's push protection is a safety net, not a plan).

License

MIT. Personal project, not affiliated with Google or YouTube. You use your own API key under your own terms of service.