Watch CLI MCP server

watch-cli

Watch any social video → get an architecture diagram, working component, runnable notebook, or step-by-step cheat sheet — automatically.

Eyes and ears for your AI agent. watch-cli composes yt-dlp + ffmpeg + a Whisper-class ASR into a single command that hands an agent the raw materials to "watch" any video: VIDEO + FRAMES + TRANSCRIPT, ready for an LLM to read frames as images and transcript as text.

watch https://twitter.com/anyone/status/12345

Works on YouTube, X, LinkedIn, TikTok, Reddit, Vimeo, and Facebook. Login-walled posts (LinkedIn, private X, FB) work with WATCH_BROWSER=auto, which reads cookies from a browser you are signed in to.

What you can build

Hand the watch output to your agent with one of five prompts in prompts/:

The prompt library is what turns "video → frames + transcript" into "video → working artifact". The full Prompt library section below has copy-paste templates.

Why this exists

Large language models can't watch video natively — they read text and look at still images. You can hand a video to a multimodal API and get back a chat-style summary, but for an agent workflow that's the wrong artifact: the agent wants the raw frames and the full transcript so it can reason for itself, not someone else's pre-digested recap.

A video is just frames + audio, and each piece already has a fast, near-free primitive:

• yt-dlp downloads from any social platform
• ffmpeg extracts evenly-spaced frames
• An ASR model transcribes the audio
• A multimodal LLM hears tone, music, SFX, language, mood

Compose them and your agent has the materials to watch any social video.

What it looks like

$ watch https://www.linkedin.com/posts/some-talk_activity-12345

VIDEO: /tmp/dl-video/abc123.mp4
DURATION: 218
FRAMES:
  /tmp/frames_abc123/frame_01.jpg
  /tmp/frames_abc123/frame_02.jpg
  …
TRANSCRIPT:
  Today I want to talk about how decomposition unlocks 10× cost reduction in
  multimodal pipelines …

Your agent reads the JPGs and the transcript. That's the whole watch.

Why pay-per-use, not subscription

Most subscription summary tools start around $15/month and deliver a polished, human-readable summary. If you're feeding an AI agent, that's the wrong artifact — agents need raw frames and the full transcript to reason for themselves, not someone else's pre-digested recap.

A typical research session is 1–3 videos, not 100. Through Kyma — the default backend — a 1-hour video costs ~$0.05 (transcribe is the only paid step; frame extraction is local ffmpeg).

No monthly minimum, no seat license, no lock-in. The free credit at Kyma signup is enough to run the full pipeline end-to-end before you spend a cent.

Install

# macOS — Homebrew (recommended)
brew tap sonpiaz/tap
brew install watch-cli

# Any OS — curl
curl -fsSL https://github.com/sonpiaz/watch-cli/releases/latest/download/install.sh | bash

The curl one-liner auto-falls back to git clone of main if no

published release tarball is reachable.

Claude Code (skill marketplace)

If you use Claude Code, install watch-cli as a skill:

/plugin marketplace add sonpiaz/watch-cli
/plugin install watch-cli@watch-cli

Shortened. The full README is on GitHub.