# YouTube Channel Database Search — Find Creators by Niche (`northglasslabs/youtube-channel-database-search`) Actor Search YouTube channels by niche keyword with optional subscriber range filters. Get subscriber counts, video counts, view counts, descriptions, and channel metadata as structured JSON. - **URL**: https://apify.com/northglasslabs/youtube-channel-database-search.md - **Developed by:** [North Glass Labs](https://apify.com/northglasslabs) (community) - **Categories:** Social media, Videos - **Stats:** 7 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.34 / 1,000 result storeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## YouTube Channel Database Search — Find Creators by Niche > Search **YouTube channels** by niche keyword and optional subscriber range. Export channel metadata: name, subscriber count, video count, total views, description, contact email, country, and joined date. Built for **influencer outreach**, **B2B lead generation**, **niche research**, and **media-buyer audience analysis**. ### What it does This Apify Actor searches YouTube's channel type-filtered results pages and extracts structured metadata for each channel found: - 🎬 **Channel name** and canonical channel URL - 👥 **Subscriber count** (parsed from `1.23M`, `450K`, etc.) - 🎥 **Video count** posted to the channel - 📊 **Total views** across all videos - 📝 **Channel description** (search-visible snippet) - 📧 **Contact email** (extracted from the channel's About page) - 🌍 **Country** (where the channel reports being based) - 📅 **Joined date** (when the channel was created) ### Why channel-level data matters Keywords surface *videos*, but for outreach and partnership decisions you need **channel** data: - Find **micro-influencers** (1K–100K subs) in a specific niche for affordable sponsorships - Build a **creator database** with emails ready for outreach campaigns - Identify **rising channels** by filtering on subscriber ranges - Segment by **country** for localized media buys - Benchmark competitors' growth using video count + total views ### Input | Field | Type | Required | Default | Description | |------------------|---------|----------|---------|------------------------------------------------------------------| | `searchQuery` | string | ✅ | — | Niche keyword or phrase (e.g. `cooking`, `tech reviews`) | | `maxResults` | integer | ❌ | `50` | Max channels to return (1–500) | | `minSubscribers` | integer | ❌ | — | Exclude channels below this subscriber count | | `maxSubscribers` | integer | ❌ | — | Exclude channels above this subscriber count | #### Example input ```json { "searchQuery": "sustainable fashion", "maxResults": 100, "minSubscribers": 5000, "maxSubscribers": 500000 } ```` ### Output Each dataset record: ```json { "channelName": "SustainableStyle Co.", "channelUrl": "https://www.youtube.com/channel/UC1234abcd", "subscriberCount": 84200, "videoCount": 412, "totalViews": 5230000, "description": "Eco-friendly fashion tips, thrift hauls, and brand reviews.", "email": "hello@sustainablestyle.co", "country": "United States", "joinedDate": "March 15, 2018" } ``` ### How it works 1. **Search** — Opens YouTube channel search with the `type=channel` filter. 2. **Paginate** — Scrolls the rendered results until the requested count is reached or the page stops growing. 3. **Parse** — Merges embedded `ytInitialData` results with rendered channel cards and removes duplicates. 4. **Filter** — Applies subscriber bounds when YouTube exposes a numeric count. Channels with hidden counts remain in the results rather than being misclassified as zero. 5. **Enrich** — Visits each surviving channel's `/about` page to extract available public details. 6. **Export** — Pushes clean records to the Apify dataset. ### Tech stack - **Python** + **Apify SDK** (`async with Actor`) - **Playwright/Chromium** for JavaScript-rendered search and About pages - **BeautifulSoup** for HTML and embedded `ytInitialData` parsing - Compact-count parsing for values such as `1.23M`, `450K`, and `2B` - Residential-proxy retries when direct access is blocked ### Use cases - **Influencer marketing agencies** building target lists by niche + subscriber tier - **B2B SaaS** doing founder-led outreach to niche creators - **Affiliate managers** identifying channels for rev-share offers - **Media buyers** segmenting creators by country and audience size - **Competitive intelligence** analysts benchmarking channel growth ### Local development ```bash cd youtube-channel-database-search python -m pip install -r requirements.txt apify run # run locally with simulated platform env apify validate-schema # validate .actor/input_schema.json apify push # deploy to Apify platform (when ready) ``` ### Notes & limitations - YouTube serves results as JavaScript-rendered pages. The Actor performs controlled scrolling, but YouTube can still cap or vary the number of channel cards returned for a query. - Subscriber bounds are applied only when YouTube exposes a numeric subscriber count; channels with hidden counts are retained with their visible subscriber text. - Email extraction depends on the channel having a public email in its About page. Many channels do not expose emails publicly. - Country and joined date depend on YouTube rendering these fields in the About page markup, which varies by channel type (brand vs personal). ### Legal & ethical notes - This actor only accesses publicly visible YouTube pages. - Respect YouTube's [Terms of Service](https://www.youtube.com/t/terms) and [robots.txt](https://www.youtube.com/robots.txt). - Use rate limits responsibly; do not overload YouTube's servers. - For production workloads, prefer the official [YouTube Data API v3](https://developers.google.com/youtube/v3). *** Generated by **Hermes Agent (Atreyu) — Autonomous Apify Engine**. # Actor input Schema ## `searchQuery` (type: `string`): Search term to find YouTube channels by niche (e.g., 'cooking', 'tech reviews', 'fitness') ## `maxResults` (type: `integer`): Maximum number of channels to extract ## `minSubscribers` (type: `integer`): Filter channels with at least this many subscribers (0 = no minimum) ## `maxSubscribers` (type: `integer`): Filter channels with at most this many subscribers (0 = no maximum) ## Actor input object example ```json { "searchQuery": "cooking", "maxResults": 50, "minSubscribers": 0, "maxSubscribers": 0 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQuery": "cooking", "maxResults": 50, "minSubscribers": 0, "maxSubscribers": 0 }; // Run the Actor and wait for it to finish const run = await client.actor("northglasslabs/youtube-channel-database-search").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQuery": "cooking", "maxResults": 50, "minSubscribers": 0, "maxSubscribers": 0, } # Run the Actor and wait for it to finish run = client.actor("northglasslabs/youtube-channel-database-search").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQuery": "cooking", "maxResults": 50, "minSubscribers": 0, "maxSubscribers": 0 }' | apify call northglasslabs/youtube-channel-database-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=northglasslabs/youtube-channel-database-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Channel Database Search — Find Creators by Niche", "description": "Search YouTube channels by niche keyword with optional subscriber range filters. Get subscriber counts, video counts, view counts, descriptions, and channel metadata as structured JSON.", "version": "0.0", "x-build-id": "UxsQJnIHoiIScG6bQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/northglasslabs~youtube-channel-database-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-northglasslabs-youtube-channel-database-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/northglasslabs~youtube-channel-database-search/runs": { "post": { "operationId": "runs-sync-northglasslabs-youtube-channel-database-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/northglasslabs~youtube-channel-database-search/run-sync": { "post": { "operationId": "run-sync-northglasslabs-youtube-channel-database-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchQuery" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Search term to find YouTube channels by niche (e.g., 'cooking', 'tech reviews', 'fitness')" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of channels to extract", "default": 50 }, "minSubscribers": { "title": "Min Subscribers", "type": "integer", "description": "Filter channels with at least this many subscribers (0 = no minimum)", "default": 0 }, "maxSubscribers": { "title": "Max Subscribers", "type": "integer", "description": "Filter channels with at most this many subscribers (0 = no maximum)", "default": 0 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```