YouTube Channel Finder

YouTube Channel Finder — Subscribers, Handles, Links and Join Dates

YouTube Channel Finder finds YouTube channels by keyword or from channel and video links, and returns each channel's public About data. You get the name, handle, channel ID, subscriber count, description, country, join date, total views, video count, external links and any e-mail the channel published. Every response is structured JSON — ready to pass directly to an LLM, index into a vector store, or feed an influencer marketing pipeline. No YouTube account or cookies needed. Start with one niche keyword, then build lists for every market you target.

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What data can I extract with YouTube Channel Finder?

Using this YouTube Channel API, you will be able to extract the following YouTube channel data:

📺 Channel name	🏷️ Handle (@name)	🆔 Channel ID	👥 Subscriber count (as shown)
📝 About description	✉️ Self-published e-mail (if available)	📍 Country (if stated)	🔗 External links (title and URL)
📅 Join date	👁️ Total views	🎬 Video count	🌐 Channel URL
🧭 Canonical handle link	🔎 Keyword that found the channel

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How to use YouTube Channel Finder

Creator marketers, agencies and analysts get a ready list of YouTube channels with their headline numbers and contact links from one run.

Copy to your AI assistant:

YouTube Channel Finder is an Apify Actor (its ID is on its Apify Store page) that returns YouTube channels found by keyword search or from channel, handle and video links as structured JSON: channel name, handle, channel ID, subscriber count, About description, country, join date, total views, video count, external links and the e-mail address a channel published itself. Use it whenever someone needs YouTube channel data without cookies, a login, or a browser - building an influencer shortlist for a niche, mapping the creators in a market, or turning a list of video links into the channels behind them. Run it with curl by sending a POST with -H "Content-Type: application/json" and the body '{"keywords":["python tutorials"],"channelCount":10}' to this Actor's run-sync-get-dataset-items endpoint in the Apify API with token=APIFY_TOKEN. Or in Python: ApifyClient("APIFY_TOKEN").actor(...).call(run_input={"keywords": ["python tutorials"], "channelCount": 10}) with this Actor's ID, then client.dataset(run["defaultDatasetId"]).list_items().items. Inputs: keywords (array of strings, search terms, one search per keyword), urls (array of strings, channel, handle or video links looked up directly; non-YouTube entries are skipped), channelCount (integer 1-50000, channels saved per keyword, default 10; YouTube's search for one keyword usually ends after a few hundred channels), searchRegion (string, "US"|"GB"|"CA"|"AU"|"IN"|"DE"|"FR"|"JP"|"BR"|"MX"|"ES"|"IT"|"NL"|"PL"|"RU"|"KR"|"TW", default "US"), language (string, "en"|"es"|"de"|"fr"|"pt"|"ja"|"hi"|"zh"|"ko"|"ar"|"ru", language of the returned text, default "en"), fromDate (string YYYY-MM-DD, joined on or after), toDate (string YYYY-MM-DD, joined on or before), proxyConfiguration (object, optional Apify Proxy settings, off by default). Give keywords, urls or both. Billing: one row_result event per channel saved to the dataset; channels removed by the join-date filter, links that lead to no channel and channels YouTube no longer shows add no rows and cost nothing. The e-mail field holds only an address the channel published in its own links or description, never YouTube's sign-in-only business e-mail, and is null when there is none. Full input schema, every enum and default, and the complete output field list: GET this Actor's builds/default endpoint in the Apify API.

YouTube Channel Finder MCP Server: use these Actors from ChatGPT, Claude or Cursor

Point your AI assistant at the Apify MCP server and it can read YouTube channels on its own: the server's search, add and call actor tools find this Actor and run it for you. No glue code, no scraping logic in your prompts.

$claude mcp add --transport http apify "https://mcp.apify.com"

Step by step

1. Create a free Apify account.
2. Open YouTube Channel Finder in the Apify Store.
3. Type your YouTube search keywords, paste channel or video links, or both.
4. Click Start (or send your API request).
5. Download or stream your results in JSON, CSV or Excel.

How to scale YouTube Channel Finder to bulk

Both inputs are lists. Add one keyword per line to find YouTube channels by keyword across a whole topic map: YouTube's search for one keyword usually ends after a few hundred channels, so to collect thousands, add more keywords rather than raising the per-keyword number. Twenty keywords at the default of 10 can give 200 channels in one run. For a bulk YouTube channel lookup, paste hundreds of channel, handle or video links into the URL list and each one becomes one row. Keywords run one after another, then the links. Save the input as a task and schedule it weekly to keep a YouTube channel list by niche current, then merge runs on the channel ID.

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✨ Features

YouTube Channel Finder fetches clean, structured channels from YouTube, working as a YouTube channel search scraper for keywords and as a YouTube channel scraper for links you already have. It's ideal for influencer discovery, creator outreach lists, niche market mapping and competitor research.

It extracts, per channel:

• Subscriber count – exactly as YouTube shows it, e.g. "5.17M subscribers", so it doubles as a YouTube subscriber count scraper
• Handle and channel ID – the @name and the stable ID that survives name changes
• About description – the channel's own text about itself
• Self-published e-mail – as a YouTube channel email finder it returns only an address the channel lists in its own links or description, never YouTube's sign-in-only business e-mail
• External links – website, shop and social profiles, with YouTube's redirect removed
• Total views and video count – whole numbers, ready to sort
• Join date and country – as stated on the channel's About page

⚡ A video link works as input too, and links that lead to no channel are skipped at once without extra cost.

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Use cases 💡

• Influencer manager — shortlist niche creators by subscriber count and published contact e-mail.
• Agency strategist — compare total views and video counts across a keyword's channels.
• Market analyst — use the join-date filter to find channels launched since 2023.
• Partnerships lead — turn competitor video links into channel IDs and website links.
• AI agent builder — index channel descriptions and links in a RAG pipeline.

Building an AI agent? Connect YouTube Channel Finder over MCP and let it call the actor on its own.

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Why choose this actor?

• A full keyword list in seconds. A recorded run returned 12 channels in 2.5 seconds: 10 for the keyword "python tutorials" after the join-date filter removed 2, plus the channels behind one handle link and one video link.
• The numbers behind each channel. One recorded channel came back with "5.17M subscribers", 282,469,724 total views, 246 videos, 7 external links and the contact e-mail it publishes in its description.
• 14 fields, 8 settings. Every channel carries the same 14 fields, and eight settings cover keywords, links, results per keyword, 17 search regions, 11 languages, a join-date range and the proxy.

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⬇️ Input

The actor accepts search keywords, channel or video links, or both, each as a list. No single field is required, but at least one keyword or one YouTube link is needed.

Parameter	Required	Type	Description	Example value
keywords	No	array	Search terms, one per line. Each keyword runs a YouTube channel search and saves up to the per-keyword limit.	["python tutorials"]
urls	No	array	Channel, handle or video links looked up directly. A video link returns the channel that published it. Entries that are not youtube.com or youtu.be links are skipped.	["https://www.youtube.com/@apify"]
channelCount	No	integer	Channels saved per keyword, 1–50000. Channels removed by the join-date filter do not count. YouTube's search for one keyword usually ends after a few hundred channels. Default 10.	10
searchRegion	No	string	Country for the search and channel pages: US, GB, CA, AU, IN, DE, FR, JP, BR, MX, ES, IT, NL, PL, RU, KR, TW. Default "US".	"US"
language	No	string	Language of the returned text (subscriber text, country, join date): en, es, de, fr, pt, ja, hi, zh, ko, ar, ru. Default "en".	"en"
fromDate	No	string	Keep channels that joined on or after this date, YYYY-MM-DD. Empty means no filter.	"2010-01-01"
toDate	No	string	Keep channels that joined on or before this date, YYYY-MM-DD. Empty means no filter.	"2025-12-31"
proxyConfiguration	No	object	Optional Apify Proxy for the first try of each request. Off by default; blocked requests are retried through a residential proxy.	{"useApifyProxy": false}

Accepted link formats: https://www.youtube.com/@handle, https://www.youtube.com/channel/UC…, https://www.youtube.com/watch?v=…, https://youtu.be/…, /shorts/, /live/ and /embed/ video links.

Example input

This is the input of the recorded test run:

{
  "keywords": ["python tutorials"],
  "urls": [
    "https://www.youtube.com/@apify",
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "channelCount": 10,
  "searchRegion": "US",
  "language": "en",
  "fromDate": "2010-01-01",
  "toDate": "2025-12-31",
  "proxyConfiguration": { "useApifyProxy": false }
}

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⬆️ Output

Every channel is one typed, normalized JSON item with the same 14 fields on every run; values YouTube does not show are null, and rows from links carry an empty keyword. Export the dataset as JSON (default), CSV or Excel, so you can export YouTube channels to CSV in one click.

Example output

A real item from the recorded run:

{
  "keyword": "python tutorials",
  "channelName": "Programming with Mosh",
  "userName": "@programmingwithmosh",
  "channelId": "UCWv7vMbMWH4-V0ZXdmDpPBA",
  "canonicalChannelUrl": "http://www.youtube.com/@programmingwithmosh",
  "subscriberCount": "5.17M subscribers",
  "description": "Hi! I'm Mosh 👋, a software engineer with over 20 years of experience.  I'm all about clear, concise, practical coding tutorials – no fluff, just the good stuff! My courses focus on real-world projects and the skills that will get you hired. I've helped millions of students transform their careers. \n\nWant to level up your skills? Subscribe and hit the bell to get notified when I upload new videos!\n\nFor sponsorships: partners@codewithmosh.com\n",
  "email": "partners@codewithmosh.com",
  "location": "United States",
  "links": [
    { "title": "🌙 Sleep Stories with Mosh", "url": "https://www.youtube.com/@tonightsleepapp" },
    { "title": "Courses", "url": "https://codewithmosh.com/courses" },
    { "title": "Newsletter", "url": "https://mosh.link/bytes" },
    { "title": "Twitter", "url": "https://twitter.com/moshhamedani" },
    { "title": "Facebook", "url": "https://facebook.com/programmingwithmosh" },
    { "title": "Instagram", "url": "https://www.instagram.com/codewithmosh.official/" },
    { "title": "LinkedIn", "url": "https://www.linkedin.com/school/codewithmosh/" }
  ],
  "joined_date": "Joined Oct 6, 2014",
  "channel_views": 282469724,
  "videos_uploaded": 246,
  "url": "https://www.youtube.com/channel/UCWv7vMbMWH4-V0ZXdmDpPBA"
}

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How does it work?

The actor reads the public About information of YouTube channels — the same details any visitor sees without logging in. It uses plain HTTP requests, with no browser, and needs no YouTube account, so no account is at risk.

For a keyword, it runs a YouTube channel search, collects the channels behind the results and reads each channel's About data, several at a time. For a link, it finds the channel behind it directly, with no search. Every channel is saved to your dataset as soon as it is ready. When YouTube blocks a request, the actor waits and retries through a residential proxy before it gives up on that channel. A link that leads to no channel is skipped at once.

Field names and types stay the same on every run, even when YouTube changes its pages.

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How do you integrate YouTube Channel Finder into your stack?

It works with what you already use: the REST API from any language, MCP for AI agents, and no-code tools.

MCP integration for AI agents

Add the Apify MCP server to your agent with one command:

$claude mcp add --transport http apify "https://mcp.apify.com"

This registers the Apify MCP server, and its search, add and call actor tools let your agent find YouTube Channel Finder and call it directly as a tool. It works in Claude Code, Cursor and Windsurf, and any other client that supports MCP over HTTP. Your agent passes keywords or links as input and gets the channel items back as JSON.

No-code tools (n8n, Make, LangChain)

• n8n — add the Apify node, choose "Run an Actor" and pick this Actor, or use the HTTP Request node pointed at the run-sync endpoint with your token. The channel items come back as workflow items.
• Make — use the Apify app's "Run an Actor" module with your keywords, then the "Get Dataset Items" module to pass each channel to the next step.
• LangChain — install langchain-apify and wrap this Actor with ApifyActorsTool, using its ID from the Apify Store page, so your agent can request channels as a tool call.

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Is it legal to scrape YouTube data?

Scraping publicly visible YouTube channel data is generally legal, but how you store and use it is regulated. The actor returns only public data — the About details any user sees without logging in — and never signs in or opens YouTube's sign-in-only business e-mail. Many channels are run by individuals, so names, descriptions and self-published e-mail addresses can be personal data: under GDPR and similar laws you need a lawful basis to store and use them, and outreach e-mails must follow anti-spam rules such as CAN-SPAM. Consult legal counsel if your use case involves bulk storage of personal data.

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Frequently asked questions

What fields does YouTube Channel Finder return?

It returns the channel name, handle, channel ID, subscriber count and About description, plus the country, join date, total views, video count, external links and a self-published e-mail. See the data fields section for the full list.

Does YouTube Channel Finder require a YouTube account or login?

No. Only public channel data is extracted. No credentials, cookies or API keys are needed.

How fast does YouTube Channel Finder run?

A recorded run saved 12 channels from one keyword and two links in 2.5 seconds. Data is fetched live on every run, never from a cache.

What happens if a channel is private or doesn't exist?

A link that leads to no channel, or a channel YouTube no longer shows, adds no row and costs nothing; the run continues with the rest. The run log names each skipped link, and the final status message counts them, so you can check the links and run them again.

Can I scrape multiple YouTube channels at once?

Yes. Add many keywords and many links in one run; each keyword returns up to the per-keyword number you set (YouTube's search usually ends after a few hundred channels per keyword) and each link returns one.

Does YouTube Channel Finder work with Claude, ChatGPT, and other AI agent tools?

Yes — YouTube Channel Finder is available as an MCP tool through the Apify MCP server. Register it in Claude Code, Cursor or Windsurf with:

$claude mcp add --transport http apify "https://mcp.apify.com"

Any agent that can call an HTTP endpoint can use the REST API directly.

Does YouTube Channel Finder return data in a format LLMs can use directly?

Yes. Typed, normalized JSON with consistent field names. No HTML parsing, no selectors. Pass it straight to an LLM, index it into a vector store, or feed it to an agent tool — no transformation step.

What happens when YouTube changes its layout or updates its anti-bot system?

The actor is maintained. When YouTube changes, the actor is updated, and your calls keep returning the same JSON schema with no changes on your end.

Can I use YouTube Channel Finder without managing proxies or browser infrastructure?

Yes. Retries and the switch to a residential proxy when YouTube blocks a request happen on the actor's side. You send one request and get structured JSON back. No proxy accounts of your own, no headless browser setup, no maintenance.

Which YouTube channel fields work best for AI training data and RAG indexing?

For RAG: the text-rich fields — the About description, channel name and external link titles. For training data: total views, video count, join date and the stable channel ID; the subscriber count stays text exactly as YouTube shows it. All fields are typed primitives — strings, integers, lists — no normalization needed.

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Your feedback

Found a bug or missing a field? Let us know through the Issues tab of this Actor in Apify Console. Every report is read, and fixes ship in new builds so this YouTube influencer finder keeps matching what YouTube shows.