MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Descripción del creador (original en inglés)
Analyze YouTube/TikTok/Instagram videos: transcripts, AI insights, tutorial extraction
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"video-url-analyzer": {
"command": "uvx",
"args": [
"video-url-analyzer-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add video-url-analyzer -- uvx video-url-analyzer-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"video-url-analyzer": {
"command": "uvx",
"args": [
"video-url-analyzer-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"video-url-analyzer": {
"type": "stdio",
"command": "uvx",
"args": [
"video-url-analyzer-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub u2n4, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.5.1) llegó al registro hace 6 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
v1.6.0 exposes 18 MCP tools:
| Tool | What it does |
|---|---|
analyze_video | Full audio + visual analysis with custom prompts. Uses Gemini multimodal understanding. |
get_transcript | Extract timestamped transcript with speaker identification. Supports 100+ languages via auto-detection. |
ask_about_video | Ask any question about the video content. |
prepare_slideshow_assets | Return ordered slideshow images as MCP image blocks so Claude/the client AI can inspect them directly. |
find_video_moments | Find matching moments with compact/standard/full structured output. |
analyze_video_segment | Analyze only a selected time range. |
prepare_video_context | Analyze once and save a reusable local context for follow-up questions and evidence lookup. |
ask_video_context | Answer from saved context by default; Gemini reanalysis is explicit opt-in. |
list_video_contexts | List saved local contexts. |
delete_video_context | Delete one saved context. |
get_video_frame | Extract a local still frame, using the YouTube fast path when possible. |
get_video_clip | Extract a short local clip, with a 30s cap and YouTube fast path when possible. |
get_video_evidence_asset | Select saved evidence and return a frame or clip reference. |
list_video_sources | Inspect local source/context/asset cache metadata. |
cleanup_video_cache | Dry-run or clean managed cache files; dry-run is the default. |
watch_and_analyze | Extract tutorial steps, shell commands, code snippets, and file paths from technical videos. |
execute_tutorial_steps | Validate and review extracted steps safely; executes only with confirmation. |
check_analysis_job | Poll background job status for TikTok/Instagram async downloads. |
| Platform | Method | Speed |
|---|---|---|
| YouTube | Direct 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 |
| TikTok | tikwm.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 |
| Page scrape via curl_cffi (fast) → yt-dlp fallback | ~10s |
| Platform | Post type | Handling |
|---|---|---|
| TikTok | Photo Mode slideshow | Downloads all images, extracts the music/audio track when available, and sends one multimodal Gemini request. |
| Carousel / single-photo posts | Downloads image slides in order and analyzes them as one post; mixed video slides are skipped with metadata. | |
| YouTube | Community /post/ image attachments | Scrapes 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.mp4is not always required: saved contexts keep the original URL, so frame/clip tools can use the local stream fast path later.
| Component | Role |
|---|---|
| Gemini 3.8 Flash | Latest Flash model, the fast default: full audio + visual understanding in a single pass |
| Gemini 4 Argon | Latest flagship reasoning model, the deep default for detail="full": text, image, video, audio and PDF input |
| FastMCP 3.x | MCP protocol framework over stdio transport |
| yt-dlp + curl_cffi | Video 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 API | TikTok fast-path fallback when yt-dlp is WAF-blocked |
| ffmpeg | Local frame/clip extraction, including YouTube stream URL extraction without full-video downloads |
| Background Jobs | Async threading for TikTok/Instagram to prevent Claude Desktop timeouts. Failed inner results are reported as failed jobs, not completed jobs. |
These are behavior modes, not tool names:
| Mode | Behavior |
|---|---|
auto | Default adaptive behavior: YouTube direct analysis; TikTok/Instagram fast API/scrape then yt-dlp fallback; saved contexts reused when available. |
api | Gemini-backed analysis or reanalysis. This is used by analysis tools and explicit Gemini opt-ins. |
client | MCP client workflow mode: long TikTok/Instagram analysis returns a background job_id for polling. |
local | Saved-context, cache, frame, and clip operations that avoid Gemini unless explicitly requested. |
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.
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:
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.
uvx (no install)uvx video-url-analyzer-mcp
Works on Windows / macOS / Linux as long as uv is on PATH.
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:
uv.uv tool install.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.VIDEO_ANALYZER_MODEL.scripts/configure_mcp_clients.ps1 for client setup.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.
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.
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.
%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 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/config.toml)[mcp_servers.video-analyzer]
command = "uvx" args = ["video-url-analyzer-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.
# Full video analysis with Gemini 3.8 Flash
analyze_video("https://www.youtube.com/watch?v=dQw4w9WgXcQ")
analyze_video("https://www.tiktok.com/@user/video/123", prompt="List every product shown and estimate prices")
get_transcript("https://www.instagram.com/reel/ABC123/", lang="ar")
ask_about_vi
Solo se muestra el principio; lee el resto en el repo