| name | video |
| description | Analyze a video (Loom, YouTube, Vimeo, TikTok, Instagram, X/Twitter, Twitch, Dailymotion, Facebook, direct URL, or local file) — transcript, key frames, OCR text, metadata, annotated timeline — and answer questions about it with timestamps. |
| argument-hint | <video-url-or-path> [question] |
| allowed-tools | Bash, Read, mcp__video-analyzer |
| homepage | https://github.com/guimatheus92/mcp-video-analyzer |
| license | MIT |
Analyze the given video and answer the user's question (or summarize it if no question was asked). Always cite timestamps (M:SS) in your answer.
Route A — video-analyzer MCP tools available (preferred)
If the video-analyzer MCP server is connected in this session, call its tools directly — do not use the CLI:
- General question or no question →
analyze_video (detail "standard")
- "What happens at X:XX" / a specific moment →
analyze_moment (time range) or get_frame_at
- Question answerable from speech alone →
get_transcript (fast, no download)
- Title / duration / views / comments only →
get_metadata (no download)
- Motion or fast UI changes →
get_frame_burst
Route B — no MCP server (any agent with a shell)
Run the one-shot CLI via Bash (first run downloads the npm package — slow is not broken; progress streams on stderr):
npx -y mcp-video-analyzer@latest analyze "<video-url-or-path>"
stdout is a single JSON document: metadata, transcript (timestamped entries), ocrResults (on-screen text), timeline, warnings, and frames — an array of { time, filePath, mimeType } pointing to JPEG key frames on disk. Then:
- Parse the JSON from stdout.
- Read the
frames[].filePath images (in parallel) when the question needs visuals.
- Answer from transcript + OCR + frames, citing timestamps.
Useful flags: --detail brief|standard|detailed (brief = metadata + transcript only, no frame extraction — the fast/cheap path), --fields metadata,transcript (filters the emitted JSON only; frames are still computed at standard detail), --max-frames <1-60>, --language <code> (force transcription language), --out <dir> (where frames are copied), --force-refresh. Run npx -y mcp-video-analyzer@latest analyze --help for the full list.
Prerequisites & degradation
- Node.js 18+ (required).
ffmpeg is bundled — no install needed.
- Platform URLs (YouTube, Instagram, TikTok, …) require
yt-dlp on PATH; direct .mp4/.webm/.mov URLs and local files work without it. Loom transcript, metadata, and comments need no yt-dlp either. Loom frames usually do — Loom serves most videos as separate DASH video+audio streams that only yt-dlp fetches and merges; a CDN fallback covers some videos without it.
- The tool never fails on partial results: the
warnings array carries actionable hints (yt-dlp install, YTDLP_COOKIES_FROM_BROWSER for Instagram/age-restricted, missing Whisper backend). Relay relevant warnings to the user instead of treating them as errors.
- An empty transcript alongside a "silent audio" warning means the video genuinely has no speech (common for muted Reels/Stories) — that is content, not a failure.
