glideit
Enables processing of YouTube videos (and other video URLs) to generate transcripts, storyboards, and high-resolution frame extracts for analysis by AI agents.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@glideitanalyze https://youtu.be/dQw4w9WgXcQ and tell me what happens at 3:15"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
glideit
Your coding agent can now watch long videos.
Paste a YouTube link (or any video URL, or a local file) and ask a question. glideit downloads the video, builds a transcript and a storyboard of the whole thing, then extracts high-res frames of just the part that matters. Your agent reads them and answers — grounded in what is actually on screen.

▶ Watch the full launch video — with narration and score (38s, made with HyperFrames from demo/demo.html)
No API keys. No cloud. Everything runs locally:
ffmpeg,yt-dlp, optionaltesseract. The agent that invoked glideit does all the "seeing" — no model API is ever called.Built for long videos. A 1-hour lecture becomes 4 storyboard images + a transcript, not 450 frames flooding the agent's context.
Reads on-screen code. High-res zoom frames + an OCR sidecar make IDE/terminal content legible.
Install
Claude Code:
/plugin marketplace add Imhari14/glideit
/plugin install glideit@glideitWhen the installer asks for a scope, pick User (the default) so
/glideitworks in every project — Project scope pins it to the folder that's open. Non-interactive:claude plugin install glideit@glideit --scope user. Installed with Project scope by mistake? Reinstall:claude plugin uninstall glideit@glideit --scope project, thenclaude plugin install glideit@glideit --scope user. New installs load on the next session — restart or reload the window.
Cursor, Codex, Copilot, Gemini CLI, and 70+ other agents:
npx skills add Imhari14/glideit -gRequirements: Python 3.10+, ffmpeg, yt-dlp (pip install yt-dlp). Run python scripts/setup.py to check. Optional: tesseract (OCR), vosk or useful-moonshine-onnx (free offline transcripts for videos without captions).
Related MCP server: llm-video-mcp
Use
In your agent, just ask:
/glideit https://youtu.be/VIDEO_ID what happens at 12:30?Or run the CLI directly:
# 1. MAP — whole-video transcript + storyboard grids
python scripts/glideit.py "https://youtu.be/VIDEO_ID"
# 2. ZOOM — dense high-res frames of one window (+ OCR of on-screen text)
python scripts/glideit.py "https://youtu.be/VIDEO_ID" --start 12:00 --end 13:30 --resolution 1024The map prints paths to transcript.txt and storyboard_*.jpg; the zoom prints per-frame paths. The agent Reads those files and answers. Everything is cached under .glideit/<hash>/ — re-runs are instant.
Options
Flag | What it does |
| zoom to a window or exact moments |
| denser sampling to catch fast motion (default ~1 frame/3s) |
| frame width — raise it to read on-screen code |
| map density ( |
| emit |
| save a note to the video's persistent |
| ignore cache and rebuild |
MCP server
mcp/server.py exposes map_video, zoom_video, and note_video to any MCP host (pip install mcp):
"glideit": { "command": "python", "args": ["mcp/server.py"] }Recreate or remix a video
--cards turns a reference video into an editable template: a structured cards.json (per-scene text, narration, timing) plus a starter HyperFrames composition. Change the content, brand, or language and render a new MP4 — then run glideit on the render to review it. The demo video above was made this way.
How it compares
claude-video's /watch is great for short clips; glideit is built for the long ones — full lectures, tutorials, conference talks — plus OCR for on-screen code and the recreate/remix bridge.
License
MIT
This server cannot be deployed
Maintenance
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