Claude Real Video

Name: Claude Real Video
Author: HUANGCHIHHUNGLeo

by HUANGCHIHHUNGLeoversion 0.10.5i★ 2,284iRuns on your computer

Registry nameio.github.HUANGCHIHHUNGLeo/claude-real-video

Overview

Description from the maker (original English)

Let any LLM watch a video locally — and search everything it has ever watched.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
UsageiGrowing★ 2,284

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

You need

PyPIPython’s uv installed (for the uvx command)

Claude DesktopClaude CodeCursorVS Code

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "claude-real-video": {
      "command": "uvx",
      "args": [
        "claude-real-video"
      ]
    }
  }
}

Run this in your terminal

claude mcp add claude-real-video -- uvx claude-real-video

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "claude-real-video": {
      "command": "uvx",
      "args": [
        "claude-real-video"
      ]
    }
  }
}

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "claude-real-video": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "claude-real-video"
      ]
    }
  }
}

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 5, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account HUANGCHIHHUNGLeo, which owns the repo
✓ Pass
Still maintained
Code last changed 13 days ago
✓ Pass
Has a licence
Uses MIT
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Needs the server’s tool list first; this check starts in the next step

Compared with others in Design, images & audioi

More stars than 93% of the other 14 servers in this category
Published to the registry more recently than 36% of the other 14 servers in this category
Basic checks equal to or better than 100% of the other 14 servers in this category

Compared only with servers in this prototype, not the whole registry.

Common questions

Is Claude Real Video safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed 13 days ago, and the latest version (0.10.5) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Figma Context MCP, Figma MCP Server, Harness

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

by GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

Harness

by autonomous-ai

Start Claude Code and Codex agents the person can watch, wait for them and read their answers.

Runs on your computer★ 1,428MITUpdated 17 days ago

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

claude-real-video

▶ [100-second demo](https://youtu.be/QRuh1oByT3M): ChatGPT and Gemini can watch video, Claude can't. Here's what Claude answers once crv turns the video into frames plus a timestamped transcript.

▶ [The 60-second pixel film — sound on](https://youtu.be/sw6_8E-57w4) (mp4 on GitHub) · an AI agent searches "how can an LLM truly understand video?", finds a key, and unlocks vision.

60-second real demo — real install, real run, real viewer.

Let Claude — or any LLM — actually watch a video.

pip install "claude-real-video[whisper]"

npx skills add HUANGCHIHHUNGLeo/claude-real-video # one command, installs the skill into Claude Code, Cursor, Codex, Copilot, Gemini CLI & 50+ agent hosts

Claude Code plugin marketplace (enable auto-update in /plugin → Marketplaces if you want it):

/plugin marketplace add HUANGCHIHHUNGLeo/claude-real-video

/plugin install claude-real-video@claude-real-video

Then paste a video link into your agent and ask about it. (CLI-only use? crv " " works with just the pip install.)

Naming: crv is the short name for claude-real-video (the PyPI package). The paid add-on, crv Pro, is sold on Capafy under the listing name "llm-real-video Pro".

▶ New: the 40-second film — *my AI agent learned to watch videos (and stopped working)*

Same 58-second clip: fixed 1 fps sampling = 58 frames. crv keeps the 26 that actually differ — and --grid packs them into 3 contact sheets. Fewer tokens, nothing missed.

**This free version lets your AI *see* the video.** crv Pro lets it *understand* it — how it was shot (cut rhythm, camera moves) plus a timestamped timeline of what frames can't show: gestures, expressions, voice pitch shifts, emotion, sound events. One-time price $29 — get it on Capafy or buy with card via Lemon Squeezy.

On Codex CLI? ▶ 36-second demo · Real Video for Codex is a self-contained build for it. You ask Codex about a video, it runs one command, then reads a SUMMARY.md with chapters, a timecoded transcript and the text that was on screen, which this free edition leaves out. So it can quote the config block on the slide at 12:40, not only what the speaker said about it, and it answers you in hh:mm:ss. Download, frames, transcription and text recognition all run on your machine, and the tool itself needs no API key and no account. Ships with the Codex skill and a crv-easy doctor self-check. Python 3.10 to 3.14, macOS or Windows 11 native. One-time $9.90: get it on Capafy or buy with card via Lemon Squeezy.

Most AI tools don't really *see* a video. Paste a YouTube link into ChatGPT and it reads the transcript, not the picture. Claude won't take a video file at all. Even Gemini, which *can* read video natively, has to send it up to Google and samples frames at a fixed interval (1 fps by default), so fast cuts slip past.

claude-real-video does it differently, and the processing runs locally: point it at a URL or a file, and it pulls the frames that *actually matter* (every scene change, not a fixed quota), throws away the near-duplicates, transcribes the audio, and hands you a clean folder any LLM can read. All the processing happens on your own machine — what gets sent anywhere is only the frames/text *you* choose to paste into an LLM afterwards.

crv "https://www.youtube.com/watch?v=..."

→ crv-out/frames/*.jpg + frames.json (per-frame timestamps) + transcript.txt/.json + MANIFEST.txt

Then drop the frames + MANIFEST.txt into Claude / ChatGPT / Gemini and ask away.

No terminal needed — run crv-web and a local page opens (Traditional Chinese / Simplified Chinese / English): paste a YouTube or Reels link or a file path, click Analyze, open the result viewer. Video analysis and output generation run on your machine — the source video never gets uploaded. (If you then paste the extracted frames or transcript into a cloud LLM, that data goes to that provider.)

Want to eyeball what the model will see first? Add --viewer — it writes a local viewer.html (video + keyframe grid + transcript) you can double-click open. No network, no extra installs.

Only part of a video matters (a 10-minute screen share inside a 90-minute call): --from 28:00 --to 43:00. ffmpeg seeks instead of decoding the whole file, Whisper only hears the window, and the frame budget is spent inside it — but every timestamp crv reports is still a source timecode you can quote to a colleague.

The meaning is small text (a terminal, a spreadsheet, an IDE): --frame-width 1600. Frame *selection* is the hard part and crv already does it; at 640px on a 1920-wide screen recording the right moment gets found and then the detail that made it worth finding is thrown away.

Slow-changing content (animation tutorials, gradual morphs, slow pans): add --adaptive — frames are picked against their rolling neighbourhood instead of a fixed threshold, so a 2-3s squash-and-stretch that never spikes any single frame still gets captured.

Text-heavy content (lecture slides, screen recordings, talking-head explainers): add --text-anchors — extra frames are forced at subtitle-cue timestamps, so each spoken segment gets a matching visual even when the scene barely changes. Needs a sidecar .srt/.vtt or an embedded subtitle track — captions burned into the pixels can't be detected. At most one forced frame per second; scene detection is untouched.

Multi-speaker content (interviews, podcasts, meetings): add --speakers — every transcript line gets a speaker label ([SPEAKER_00], [SPEAKER_01], …) so the model can follow who said what. Runs a local diarization model (45 MB, downloads once, no account or token needed). Install with pip install "claude-real-video[speakers]".

Not doing LLM work? It also works as a general-purpose video keyframe extractor — scene-change detection + dedup, no ML models to download.

Using Claude Code — or any coding agent? One command installs the skill (works with Claude Code, Cursor, Codex, Copilot, Gemini CLI and other agentskills.io-compatible hosts):

pip install "claude-real-video[whisper]"

npx skills add HUANGCHIHHUNGLeo/claude-real-video

Then just paste a video link into your agent and ask about it.

Manual install (clone + copy)

git clone https://github.com/HUANGCHIHHUNGLeo/claude-real-video.git

mkdir -p ~/.claude/skills && cp -r claude-real-video/skills/claude-real-video ~/.claude/skills/

**Tell it *why* you're watching, and keep what it finds:**

crv "https://youtu.be/..." --why "find the pricing strategy" --kb ~/notes

--why makes the analysis focus on what you care about instead of a generic summary; --kb saves the result as a dated note in your own notes folder, so it doesn't die in crv-out.

New in 0.10.x — analyse only the part that matters:

crv long-meeting.mp4 --from 28:00 --to 43:00

--from / --to cut a window out of a long video: ffmpeg seeks instead of decoding the whole file, the transcript and frame budget follow the window, and every reported timestamp is still a source timecode you can quote back to the original.

Measured numbers

Real run on a 3-minute 640x360 video (benchmark/jfk-rice.mp4), Mac mini M4, local CPU, frames + dedup only (--no-transcribe). Image tokens estimated with Anthropic's (width x height) / 750 — 307 tokens/frame at 640x360.

Mode	Frames kept	Wall time	Est. image tokens
default (scene-change + 1s floor)	170 (from 180 extracted)	23.5 s	~52k
`--max-frames 80`	80	23.4 s	~25k
`--adaptive` (catches slow morphs)	270	36.8 s	~83k

Dedup v0.7.16 — small-subject fast action no longer disappears. A percentage comparator is structurally blind to a subject that covers <1% of the frame (it can never change 8% of the pixels). Found in a user's 2,181-video batch run; fixed with a third "action channel". Synthetic repro — static 1280x720 shot, a 40x90 px subject (0.4% of frame) moves fast only in the last 10 of 65 frames:

	Frames kept	Action frames survived
v0.7.15	2	1 / 10
v0.7.16	11	10 / 10 — full trajectory

Why not just sample frames?

Most "let an LLM watch a video" scripts (and Gemini's own pipeline) grab frames at a fixed interval — e.g. one per second. That over-samples a static screencast and under-samples a fast-cut reel. claude-real-video is smarter:

	fixed-interval sampling	claude-real-video
Frame selection	every N seconds	scene-change detection + density floor
Repeated shots (A-B-A cuts)	sent again every time	sliding-window dedup sends each shot once
Static slide (10 min)	~600 near-identical frames	collapses to 1 (dedup)
Fast-cut reel	misses frames between samples	catches each visual change
Audio	often ignored	Whisper transcript w/ language detect
Where the processing happens	often in someone's cloud	on your machine (you choose what to share with an LLM afterwards)
Input	usually local file only	URL (yt-dlp) or local file

You feed the model *fewer, more meaningful* frames — cheaper context, better understanding.

Install

pip install "claude-real-video[whisper]"   # recommended: frames + dedup + audio transcription

pip install claude-real-video # core only (frames + dedup)

pip extras never install themselves — without [whisper] there is no speech-to-text (videos that ship their own subtitles still get a transcript).

System requirement: ffmpeg

ffmpeg / ffprobe are used for frame extraction and audio, and aren't pip-installable. Install them once:

OS	command
macOS	`brew install ffmpeg`
Linux	`sudo apt install ffmpeg` (or your distro's package manager)
Windows	`winget install Gyan.FFmpeg` — or `choco install ffmpeg` — or download a build and add its `bin\` folder to your `PATH`

Verify it's on your PATH:

ffmpeg -version

Transcription uses the whisper CLI (installed by the [whisper] extr

Only the beginning is shown; read the rest in the repo

Claude Real Video

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Figma MCP Server

Harness

README from the maker

claude-real-video

→ crv-out/frames/*.jpg + frames.json (per-frame timestamps) + transcript.txt/.json + MANIFEST.txt

Measured numbers

Why not just sample frames?

Install

System requirement: ffmpeg