MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Descripción del creador (original en inglés)
Social Analyzer - Find Social Media by Username | Sherlock
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.
AuthorizationLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Esta dirección necesita una clave en un header de la solicitud, y el menú para agregar conectores no puede ponerla. Usa Claude Code, Cursor o VS Code.
Ejecuta esto en tu terminal
claude mcp add --transport http social-analyzer 'https://mcp.apify.com/?tools=anshumanatrey/social-analyzer' --header 'Authorization: your-value'Completa los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"social-analyzer": {
"url": "https://mcp.apify.com/?tools=anshumanatrey/social-analyzer",
"headers": {
"Authorization": "your-value"
}
}
}
}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": {
"social-analyzer": {
"type": "http",
"url": "https://mcp.apify.com/?tools=anshumanatrey/social-analyzer",
"headers": {
"Authorization": "your-value"
}
}
}
}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.
Esta dirección necesita una clave en un header de la solicitud, y el menú para agregar conectores no puede ponerla. Usa Claude Code, Cursor o VS Code.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Authorization secreto obligatorio HTTP headerEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
El servidor pide iniciar sesión antes de mostrar sus herramientas.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub AnshumanAtrey, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Respondió en 79 ms (HTTP 401)
Declara inicio de sesión con OAuth, así que tu app de IA puede llevarte a iniciar sesión
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
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 3 de 3 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.
Debes completar: Authorization
Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
El repo de GitHub cambió por última vez –, y la última versión (1.0.14) llegó al registro hace 8 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
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:★ 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.
Type a username and get every public profile that uses it. Every run checks all 999 sites the scanner knows: social networks, gaming, dating, developer, forums, wikis and niche platforms. Every hit is ranked high, medium or low confidence with the page's title, language and meta tags, so real profiles come first and guesses stay marked. No login, no cookies, no API key.
Available as an Apify Actor. $0.005 per profile found. One username on all 999 sites takes about 3 minutes; on the 100 most popular sites about 30 seconds.
You give it one username, or a list, and nothing else is needed: with only the username set, the scan is the widest possible, all 999 sites, worldwide, every category, every match kept and labelled by confidence, page details and patterns extracted, one hour to do it. It checks those sites for a profile with exactly that handle and returns one row per profile it finds: the platform, the profile URL, how confident the match is, the site's category and country, the page title, its language and its meta tags. A summary row and an OUTPUT record say in plain words what was checked, how many sites had no profile, how many did not answer, and what came back.
You can paste @elonmusk or a full profile link like twitter.com/elonmusk; the handle is taken out of it. If you paste an email address, the part before the @ is searched and the run points you to the email tool for the address itself. A full name like John Smith is searched as johnsmith, and the summary names john.smith and john_smith to try next.
| Sherlock CLI | This actor | |
|---|---|---|
| Setup | pip install, Python, terminal | Open the page, type a handle, press Start |
| Input | One exact handle | Handles, @handles, profile links, lists of up to 25 |
| Sites covered | About 300 | 999, checked in parallel |
| Confidence | Found or not found | High, medium, low, with the match rate |
| Filtering | None | Category, country, named sites |
| Output | Terminal text | One row per profile with category and country, CSV or JSON |
The scanner underneath is qeeqbox/social-analyzer (3,000+ GitHub stars). This actor runs it at full depth on every run: all sites, all output fields, 60 parallel workers instead of its hardcoded 15, and its most permissive detection level. It also chooses the sites itself from the scanner's own list and fixes what the command line gets wrong in the current version: several usernames at once, category and country filters, a confidence filter that silently did nothing, and the slow and special modes that have no code behind them.
| Event | Free and Starter plans | Scale plan | Business plan and above | When it is charged |
|---|---|---|---|---|
Profile found | $0.005 | $0.0045 | $0.004 | Per profile row, charged as each step of the scan delivers its rows. The summary row is free. |
Apify Store discounts: on the Scale plan you pay 10% less, on Business and above 20% less.
Typical runs (Free and Starter price):
| Job | Cost |
|---|---|
| One username, all 999 sites, everything kept: 108 confident plus possible and weak rows, about 150 rows (the prefill) | $0.75 |
| One username, 100 most popular sites, 17 profiles found | $0.09 |
| Two usernames on the 48 adult and dating sites, 16 profiles (a real run) | $0.09 |
| 25 usernames, 100 sites each, about 30 profiles each | $3.76 |
A run that finds nothing costs nothing. A form with no usable username stops before anything is charged. If your spending limit cannot pay for one profile, nothing is searched or charged and the status message gives the limit and the price. If a run is cut off by the time limit or your spending limit, you keep and pay for only the rows delivered before the cut.
| Field | Required | What it does |
|---|---|---|
username | one of the two | The handle. Paste @handle or a profile link; separate several with commas. |
usernames | one of the two | A list of handles, one per line, up to 25 per run. |
top | no | How many of the most popular sites to check. Default and maximum 999 (all of them); lower it for a quicker run. |
websites | no | Only these sites, by domain or partial name: github.com, reddit. Any of the 999 sites. |
siteType | no | Every category by default. One category: social, adult_dating, gaming, developer_tech, forums, wikis_reference, entertainment, photo_design, news_blogs, shopping, jobs_business, education, other. |
countries | no | Worldwide by default. Only sites based in these countries, by name (United States, India, Russia, Japan and 19 more). |
filter | no | all (everything, marked by confidence, default), good,maybe (50% and up), good (100% matches only). |
metadata | no | Add each confident profile's meta tags and detected page language. Default on. |
extract | no | Pull emails, links and patterns from found pages. Default on. |
timeout | no | Time limit in seconds for the whole run. Default and maximum 3600. |
Filters combine. With a category or country filter, top picks the most popular sites inside that filter. With websites, top is ignored.
Nothing is held back. The scanner offers three modes; only fast has code behind it in the current version, and its internal "extreme" level is a stricter gate that returns fewer hits, not a deeper scan. So every run already uses the deepest configuration that exists: all sites, all fields, the permissive level. The only feature not exposed is profile screenshots, which needs a Chrome browser the image does not carry.
The status line at the top of the run updates after every step: 48% done: 500 of 998 site checks, 143 profiles so far. 1 of 3 usernames finished, now checking kaytats. Rows appear in the dataset as each step (about 125 sites) finishes, so you can start reading results after about 30 seconds. The OUTPUT record carries status, percentDone and per-username progress while the run is going, and turns into the final summary when it ends.
Real rows from a local run on 2026-09-12 with input {"username": "frostkatrina@ymail.com", "top": 50}. The address was recognised as an email, the handle frostkatrina was searched, 17 profiles came back in 37 seconds.
| Username | Platform | Profile URL | Confidence | Match % | Category | Site country | Adult site |
|---|---|---|---|---|---|---|---|
| frostkatrina | facebook.com/frostkatrina | high | 100 | social | United States | no | |
| frostkatrina | pinterest.com/frostkatrina | high | 100 | social | United States | no | |
| frostkatrina | Fandom | fandom.com/u/frostkatrina | medium | 66.7 | entertainment | United States | no |
| frostkatrina | instagram.com/frostkatrina | medium | 66.7 | social | United States | no |
One profile row as JSON:
{
"recordType": "profile", "username": "torvalds", "platform": "GitHub", "site": "github.com", "link": "https://github.com/torvalds", "confidence": "high", "matchRate": 100.0, "category": "developer_tech", "categoryDetail": "Computers Electronics and Technology > Programming and Developer Software", "country": "United States", "adultSite": false, "siteRank": 89, "pageTitle": "torvalds (Linus Torvalds)", "language": "English", "metadata": [{"property": "og:title", "content": "torvalds - Overview"}, {"property": "og:type", "content": "profile"}], "checkedAt": "2026-09-12T14:20:11+00:00" }
The summary row (also saved as the OUTPUT record) from the same email run:
{
"recordType": "summary", "usernames": ["frostkatrina"], "usernamesChecked": 1, "sitesPerUsername": 50, "filters": {}, "profilesFound": 17, "highConfidence": 2, "mediumConfidence": 11, "lowConfidence": 4, "sitesNotFound": 29, "sitesFailed": 4, "durationSeconds": 36.5, "notes": ["\"frostkatrina@ymail.com\" is an email address. Searched the part before the @ (\"frostkatrina\") as a username. To find accounts registered with the email itself, use https://apify.com/anshumanatrey/holehe-email-osint"], "message": "Found 17 profiles for frostkatrina across 50 sites: 2 high, 11 medium, 4 low confidence. Strongest first. ..." }
Confidence. High means a 100% match: the site answered exactly the way it does for a real profile. Medium (50 to 99%) is likely but worth a look; many adult and dating sites answer at 50% for any handle. Low is a guess. Rows are sorted strongest first. The default keeps everything, so a bare username misses nothing; choose "Confident and possible" or "Confident matches only" for a cleaner list.
Q: I typed several usernames and got one weird result. Separate them with commas or use the bulk list. Each username is checked on its own. Usernames have no spaces, so a full name such as John Smith is searched as johnsmith, and the summary names john.smith and john_smith to add if you want those forms too.
Q: I pasted an email address. The run searches the part before the @ as a username and tells you so in the summary. To find which sites an email is registered on, use holehe-email-osint.
Q: I picked a category and a country that have no site in common. Filters only narrow, so a filter that would leave nothing to check is left out and the run says so. None of the 48 adult and dating sites is based in India, for example, so all 48 are checked and the status message tells you where they are based. The same goes for a named site that is not in the list. Category counts are shown in the dropdown; most sites in the list are American or Indian.
Q: Can I run it with less memory? Yes. Each step of the scan is its own process of about 300 MB, and the run starts as many at once as its memory holds: 8 at the default 4 GB, 5 at 2 GB, 1 at 1 GB. Less memory is slower, not broken. A step that still comes back empty is retried on its own, and any sites that could not be checked are counted in the summary (sitesNotChecked) with the reason, never reported as "no profile".
Q: My run found nothing. The status message says so plainly, and the summary tells you how many sites had no profile and how many did not answer. Check the spelling, or switch to "Confident and possible matches" to see weaker matches. A handle that exists nowhere returns one summary row.
Q: Some results are wrong. Sites that answer with a normal page for any handle produce medium matches. Stay on "Confident matches only" for clean lists, and check medium rows by hand.
Q: Does it check dating and adult sites? Yes, always. The scanner's list has 48 of them and they are part of every run; the adultSite column marks those rows, and the "Adult and dating sites" category checks only them.
Q: Can I see progress, or get results before the run ends? Yes. The status line shows the percentage done and the counts, rows arrive step by step, and the OUTPUT record has percentDone for API users. You pay per step as its rows are delivered, never for work that was cut off.
Q: Where did slow and special modes go? The scanner's command line only has code for fast; slow and special return nothing in version 0.45. Every run here is already the deepest scan that exists (all 999 sites, every field). API calls th
Solo se muestra el principio; lee el resto en el repo