Skip to main content
Glama
guimatheus92

mcp-video-analyzer

by guimatheus92
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

analyze_video

Read-onlyIdempotent

Extract transcript, key frames, OCR text, and annotated timeline from video URLs. Supports Loom, YouTube, direct files, and more.

Instructions

Analyze a video URL to extract transcript, key frames, metadata, comments, OCR text, and annotated timeline.

Returns structured data about the video content:

  • Transcript with timestamps and speakers

  • Key frames extracted via scene-change detection (deduplicated, as images). For static clips with no scene cuts (e.g. talking-head Reels/Stories where only on-screen text changes) it automatically falls back to uniform temporal sampling.

  • OCR text extracted from frames (code, error messages, UI text, prices/dates/CTAs visible on screen)

  • Annotated timeline merging transcript + frames + OCR into a unified chronological view

  • Metadata (title, duration, platform)

  • Comments from viewers (if available)

Supports: Loom (loom.com/share/...), YouTube/Vimeo/TikTok/Instagram/X/Twitch/Dailymotion/Facebook (requires yt-dlp), direct video URLs (.mp4, .webm, .mov), and local video files (absolute path or file:// URI).

Detail levels:

  • "brief": metadata + truncated transcript only (fast, no video download)

  • "standard": full analysis with scene-change frames (default)

  • "detailed": dense sampling (1 frame/sec), more frames, full OCR

Use options.fields to request only specific data (e.g., ["metadata", "transcript"]). Use options.forceRefresh to bypass the cache. Use options.model / options.language / options.initialPrompt to override Whisper transcription per call (e.g. a heavier model + a domain glossary for hard audio) without restarting the server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesVideo source: Loom share link, platform video URL (YouTube, Vimeo, TikTok, Instagram, X, Twitch, Dailymotion, Facebook), direct .mp4/.webm/.mov URL, or absolute path to a local video file
optionsNoAnalysis options

Tool Definition Quality

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already indicate readOnlyHint, idempotentHint, and non-destructive behavior. The description adds significant behavioral details: scene-change detection with fallback to uniform sampling for static clips, caching behavior, and platform-specific support. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: purpose, outputs, supported sources, detail levels, and options. Every sentence adds value, and it is appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (many parameters, nested options, no output schema), the description is thorough. It explains all key aspects: return data, caching, platform support, detail levels, and how to customize analysis. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description enriches parameter understanding by explaining detail levels, maxFrames default scaling, threshold sensitivity for different video types, ocrLanguage format, and initialPrompt usage for domain-specific transcripts. This goes well beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze a video URL to extract transcript, key frames, metadata, comments, OCR text, and annotated timeline.' It lists specific outputs and distinguishes itself from sibling tools like get_frames or get_transcript by being a comprehensive analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance through detail levels ('brief', 'standard', 'detailed') and options like 'fields' to limit output. It also explains when to use options like 'forceRefresh' or 'initialPrompt'. However, it does not explicitly contrast with sibling tools (e.g., when to use get_frames instead).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/guimatheus92/mcp-video-analyzer'

If you have feedback or need assistance with the MCP directory API, please join our Discord server