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Video URL Analyzer

by u2n4version 1.5.1i★ –iRuns on your computer
Registry nameio.github.u2n4/video-url-analyzer-mcp

Install

Overview

Description from the maker (original English)

Analyze YouTube/TikTok/Instagram videos: transcripts, AI insights, tutorial extraction

PopNx MCP’s three pillars

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

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: Marketing & social media

Install

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

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

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

{
  "mcpServers": {
    "video-url-analyzer": {
      "command": "uvx",
      "args": [
        "video-url-analyzer-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add video-url-analyzer -- uvx video-url-analyzer-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "video-url-analyzer": {
      "command": "uvx",
      "args": [
        "video-url-analyzer-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "video-url-analyzer": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "video-url-analyzer-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

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

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account u2n4, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – 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

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

  • More stars than 0% of the other 3610 servers in this category
  • Published to the registry more recently than 9% of the other 3610 servers in this category
  • Basic checks equal to or better than 100% of the other 3610 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Video URL Analyzer safe?

It passed 1 of 1 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 –, and the latest version (1.5.1) reached the registry 6 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: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

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

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

MCP YouTube Transcript

An MCP server retrieving transcripts of YouTube videos

by jkawamotoGrowing★ 495Updated 11 days ago

Runs on your computer

Google Analytics MCP

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

by surendranbGrowing↓ 1.1K/wk★ 244Updated 11 days ago

Runs on your computer

BibiGPT YouTube Video Summarizer

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

by JimmyLvGrowing★ 137Updated 12 days ago

Runs in the cloud✓ bibigpt.co

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.

Video Analyzer MCP Server

Analyze any video with AI — YouTube, TikTok & Instagram

Powered by Google Gemini 3.8 Flash · FastMCP · yt-dlp

Features · Architecture · Quick Start · Integration · Security · العربية


Features

v1.6.0 exposes 18 MCP tools:

ToolWhat it does
analyze_videoFull audio + visual analysis with custom prompts. Uses Gemini multimodal understanding.
get_transcriptExtract timestamped transcript with speaker identification. Supports 100+ languages via auto-detection.
ask_about_videoAsk any question about the video content.
prepare_slideshow_assetsReturn ordered slideshow images as MCP image blocks so Claude/the client AI can inspect them directly.
find_video_momentsFind matching moments with compact/standard/full structured output.
analyze_video_segmentAnalyze only a selected time range.
prepare_video_contextAnalyze once and save a reusable local context for follow-up questions and evidence lookup.
ask_video_contextAnswer from saved context by default; Gemini reanalysis is explicit opt-in.
list_video_contextsList saved local contexts.
delete_video_contextDelete one saved context.
get_video_frameExtract a local still frame, using the YouTube fast path when possible.
get_video_clipExtract a short local clip, with a 30s cap and YouTube fast path when possible.
get_video_evidence_assetSelect saved evidence and return a frame or clip reference.
list_video_sourcesInspect local source/context/asset cache metadata.
cleanup_video_cacheDry-run or clean managed cache files; dry-run is the default.
watch_and_analyzeExtract tutorial steps, shell commands, code snippets, and file paths from technical videos.
execute_tutorial_stepsValidate and review extracted steps safely; executes only with confirmation.
check_analysis_jobPoll background job status for TikTok/Instagram async downloads.
Supported Platforms
PlatformMethodSpeed
YouTubeDirect Gemini analysis — no download needed for analysis. Frame/clip extraction uses yt-dlp -g stream URLs + ffmpeg when available, with a small section-download fallback.Instant / fast local extraction
TikToktikwm.com API (fast) → yt-dlp fallback with a safe MP4 H.264/H.265 selector that avoids unsupported ByteDance bvc2/bytevc2 streams when possible~8s
InstagramPage scrape via curl_cffi (fast) → yt-dlp fallback~10s
Photo / Slideshow Posts
PlatformPost typeHandling
TikTokPhoto Mode slideshowDownloads all images, extracts the music/audio track when available, and sends one multimodal Gemini request.
InstagramCarousel / single-photo postsDownloads image slides in order and analyzes them as one post; mixed video slides are skipped with metadata.
YouTubeCommunity /post/ image attachmentsScrapes ytInitialData, downloads image attachments, and analyzes them through Gemini Files API.

YouTube videos are analyzed directly through Gemini's native video understanding — zero download, zero upload, maximum speed.

For YouTube evidence assets, source.mp4 is not always required: saved contexts keep the original URL, so frame/clip tools can use the local stream fast path later.


Architecture

ComponentRole
Gemini 3.8 FlashLatest Flash model, the fast default: full audio + visual understanding in a single pass
Gemini 4 ArgonLatest flagship reasoning model, the deep default for detail="full": text, image, video, audio and PDF input
FastMCP 3.xMCP protocol framework over stdio transport
yt-dlp + curl_cffiVideo download with Chrome browser impersonation to bypass anti-bot. TikTok downloads prefer locally decodable MP4 H.264/H.265 formats and reject ByteDance bvc2/bytevc2 streams.
tikwm.com APITikTok fast-path fallback when yt-dlp is WAF-blocked
ffmpegLocal frame/clip extraction, including YouTube stream URL extraction without full-video downloads
Background JobsAsync threading for TikTok/Instagram to prevent Claude Desktop timeouts. Failed inner results are reported as failed jobs, not completed jobs.
Operating Modes

These are behavior modes, not tool names:

ModeBehavior
autoDefault adaptive behavior: YouTube direct analysis; TikTok/Instagram fast API/scrape then yt-dlp fallback; saved contexts reused when available.
apiGemini-backed analysis or reanalysis. This is used by analysis tools and explicit Gemini opt-ins.
clientMCP client workflow mode: long TikTok/Instagram analysis returns a background job_id for polling.
localSaved-context, cache, frame, and clip operations that avoid Gemini unless explicitly requested.

Quick Start

The packaged runtime lives at src/video_url_analyzer_mcp/server.py; the console entry point is video_url_analyzer_mcp:main. Pick whichever install path matches your workflow.

Option A — one-line Windows installer (recommended for new users)
irm https://raw.githubusercontent.com/u2n4/video-url-analyzer-mcp/main/install.ps1 | iex

The installer follows the current MCP client pattern: it installs/runs from PyPI with uvx, uses an existing GEMINI_API_KEY environment variable when one is already set, otherwise asks for the key only through a hidden prompt, and lets the user choose where to register the server:

  • Claude Code
  • Claude Desktop
  • Codex CLI
  • Cursor
  • Windsurf
  • VS Code / GitHub Copilot
  • Google Antigravity
  • Cline

Do not append your API key to the PowerShell command. If you skip the key, the installer still registers the server and you can set GEMINI_API_KEY later. If GEMINI_API_KEY is already set in your User environment, the installer will use it directly and print only a masked form like AIza...abcd.

Option B — uvx (no install)
uvx video-url-analyzer-mcp

Works on Windows / macOS / Linux as long as uv is on PATH.

Option C — Windows wizard from a checkout
git clone https://github.com/u2n4/video-url-analyzer-mcp.git

cd video-url-analyzer-mcp powershell -ExecutionPolicy Bypass -File scripts\install_windows.ps1

The wizard:

  • Verifies Python 3.10+ and (optionally) uv.
  • Installs the package as an editable checkout or via uv tool install.
  • Lets you save GEMINI_API_KEY to a User environment variable or to a gitignored .env.keys.local. Keys are never printed; the wizard shows only their length.
  • Lets you pick a default model via VIDEO_ANALYZER_MODEL.
  • Runs an offline import smoke test.
  • Hands off to scripts/configure_mcp_clients.ps1 for client setup.
Option D — Manual install (any OS)
git clone https://github.com/u2n4/video-url-analyzer-mcp.git

cd video-url-analyzer-mcp pip install -e . python -m video_url_analyzer_mcp

Get a free key at Google AI Studio, then set it once in your shell environment (setx GEMINI_API_KEY ... on Windows, or your ~/.zshrc / ~/.bashrc on macOS/Linux). For local dev only, you can also put it in a gitignored .env file in the repo root. The server reads .env. start.bat also reads .env.keys.local, which the wizard writes.

Windows launcher

start.bat loads .env.keys.local (if present), sets VIDEO_ANALYZER_MODE=auto when it is unset, and runs python -m video_url_analyzer_mcp. It sets no model id, so the model variables from your environment or .env apply, as the table below describes. Use it as a command value in any MCP client that prefers a single executable.


Integration

Run scripts/configure_mcp_clients.ps1 for an interactive menu, or copy the snippets below from docs/mcp-config-examples.md. The wizard backs up existing client config, validates JSON/TOML, and never overwrites unrelated MCP servers.

Client configs use video-analyzer as the local MCP server entry name. The published package remains video-url-analyzer-mcp, and the registry name remains io.github.u2n4/video-url-analyzer-mcp.

Claude Desktop (%APPDATA%\Claude\claude_desktop_config.json)
{

"mcpServers": { "video-analyzer": { "command": "uvx", "args": ["video-url-analyzer-mcp"] } } }

The wizard prefers leaving the API key in your OS environment. If you must embed it, add "env": { "GEMINI_API_KEY": "YOUR_KEY_HERE" }.

Claude Code (CLI)
claude mcp add video-analyzer --transport stdio -- uvx video-url-analyzer-mcp

Or, after pip install -e . in the repo:

claude mcp add video-analyzer --transport stdio -- python -m video_url_analyzer_mcp
Codex CLI (~/.codex/config.toml)
[mcp_servers.video-analyzer]

command = "uvx" args = ["video-url-analyzer-mcp"]

VS Code / GitHub Copilot MCP

Workspace registration writes .vscode/mcp.json:

{

"inputs": [ { "type": "promptString", "id": "video-url-analyzer-gemini-api-key", "description": "Gemini API key for video-url-analyzer-mcp", "password": true } ], "servers": { "video-analyzer": { "type": "stdio", "command": "uvx", "args": ["video-url-analyzer-mcp"], "env": { "GEMINI_API_KEY": "${input:video-url-analyzer-gemini-api-key}" } } } }

For all clients, restart the application after editing config so the new MCP server is picked up. Full snippets — including Cursor, Windsurf, Antigravity (%USERPROFILE%\.gemini\antigravity\mcp_config.json), and Cline — live in docs/mcp-config-examples.md.


Usage Examples

# Full video analysis with Gemini 3.8 Flash

analyze_video("https://www.youtube.com/watch?v=dQw4w9WgXcQ")

Custom analysis prompt

analyze_video("https://www.tiktok.com/@user/video/123", prompt="List every product shown and estimate prices")

Multilingual transcript extraction

get_transcript("https://www.instagram.com/reel/ABC123/", lang="ar")

Ask specific questions about video content

ask_about_vi

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

Ask PopNx