---

name: scribiz description: Get the transcript, on-screen text, summary, and chapters of any video or audio with Scribiz. Use when the user wants to transcribe a YouTube, TikTok, Instagram, podcast, or local media file, generate SRT or VTT subtitles, summarize a video, ask questions about a video, or turn a video into a blog post, show notes, or social posts. metadata: version: 1.0.0 author: illyism source: https://il.ly/skills/scribiz

Scribiz

Scribiz turns a video or audio link, or a local file, into a transcript with speakers and timestamps, the text shown on screen, a summary, and chapters. It works when a video has no captions.

Docs: scribiz.com/docs. Every docs page is also Markdown: add .md to the path.

Pick a way in

What does the agent have?
├── An MCP client (Claude Code, Cursor, Codex) and a link
│   └── Use the MCP server. Best for questions, summaries and search.
├── A shell and a link or local file
│   └── Use the CLI. Best for subtitles, files on disk and batch jobs.
└── Neither
    └── Send the user to scribiz.com to paste the link.

MCP server

Hosted at https://scribiz.com/mcp (Streamable HTTP). No key needed to start.

# Claude Code
claude mcp add --transport http scribiz https://scribiz.com/mcp

Cursor, in ~/.cursor/mcp.json:

{ "mcpServers": { "scribiz": { "url": "https://scribiz.com/mcp" } } }

# Codex: ~/.codex/config.toml
[mcp_servers.scribiz]
url = "https://scribiz.com/mcp"

Tools:

• get_video_context: summary, chapters and key moments in under 2,000 tokens. Start here.
• search_video: find where a phrase is said and read only those minutes.
• ask_video: an answer with 3–5 cited moments, each a timestamp link.
• get_transcript: the full transcript, when you really need all of it.
• get_job: check a running job.

Without a key the server reads captions, videos already processed and, within a small daily allowance, the link itself. It never looks at the picture. With an API key (Authorization: Bearer $SCRIBIZ_API_KEY) it uses the account's minutes and can read the screen. Other clients: MCP install.

Prefer get_video_context then search_video over pulling the whole transcript. A two-hour talk is more than 25,000 tokens.

CLI

npm install -g scribiz     # or: npx scribiz --help
scribiz login              # free account, 30 minutes a month
scribiz setup              # or: your own Gemini API key
scribiz doctor             # checks the credential, ffmpeg, ffprobe, yt-dlp

Needs Node.js 24+, ffmpeg, and yt-dlp for most links (brew install ffmpeg yt-dlp). Tested on macOS.

scribiz "https://www.youtube.com/watch?v=VIDEO_ID" -o talk.srt        # subtitles
scribiz talk.mp4 -f txt -o talk.txt                                    # plain text
scribiz talk.mp4 -f md -o talk.md                                      # Markdown with speakers
scribiz context talk.mp4 --visual -f context                           # transcript + on-screen notes + summary + chapters, for an LLM
scribiz talk.mp4 --json --out-file talk.json                           # save the full result once
scribiz format talk.json -f vtt                                        # render another format without paying again
scribiz ask talk.json "What did they decide about pricing?"

Put links that contain ? in quotes. A folder input writes one .srt next to each file.

Options

• Format: -f srt|vtt|txt|md|context|json (default srt)
• Mode: -m auto|captions|audio|visual|full (aliases listen, watch, both). Auto uses good captions and listens when there are none.
• Speakers: --speakers for interviews and podcasts, --no-speakers for on-screen captions
• Proofread: --proofread, plus --vocabulary "Brand,Name" for names speech-to-text mishears
• Language hint: -l en
• Cost guard: --max-cost 0.50, --max-duration 02:00:00
• Scripts: --no-input never prompts. Exit codes: 0 ok, 2 usage, 3 sign-in or quota, 4 source, 5 provider, 6 missing tool.

Do not split or rechunk SRT cues after the fact. Re-run Scribiz instead.

Content workflows

• Video to blog post: run get_video_context (or scribiz context), outline from the chapters, quote the transcript for key claims, and link timestamps as sources.
• Podcast show notes: -f md --speakers, then write a summary, chapter list with timestamps, and pull quotes.
• Social clips: use search_video to find the strongest moments, then write posts that cite the exact second.
• Competitor research: summarize a competitor's demo or webinar and list the claims and features they show on screen (--visual).
• Subtitles for upload: --proofread --no-speakers -o video.srt.

Limits

• YouTube, podcast feeds, direct media links and files work best. TikTok, X and Vimeo are best effort. Instagram usually needs --cookies-from-browser chrome on the CLI.
• Not for live streams, DRM services (Spotify, Netflix), editing, or generating video.
• Spot-check names and brands in the output before publishing.