# YouTube Channel Intelligence (`viniman27/youtube-channel-intelligence`) Actor Monitor public YouTube channel RSS feeds and enrich recent videos for trend scouting, lead discovery, creator research, and content intelligence. - **URL**: https://apify.com/viniman27/youtube-channel-intelligence.md - **Developed by:** [Vinicius Assumpรงรฃo de Araujo](https://apify.com/viniman27) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 2 total users, 0 monthly users, 88.9% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Intelligence Monitor public YouTube channel RSS feeds and enrich recent videos for trend scouting, content intelligence, creator research, and lead discovery. No login, no browser, no proxy. Uses public YouTube RSS feeds only. # Actor input Schema ## `channelIds` (type: `array`): Public YouTube channel IDs to monitor via RSS. ## `feedUrls` (type: `array`): Optional full YouTube RSS feed URLs. Use when channel ID is already embedded in a feed URL. ## `keywords` (type: `array`): Keywords used to tag and score videos. ## `maxResults` (type: `integer`): Maximum number of enriched videos to output. Keep small for cheap runs. ## `minScore` (type: `integer`): Only output videos with opportunity_score greater than or equal to this value. ## `includeSummary` (type: `boolean`): Store a SUMMARY record in the default key-value store. ## Actor input object example ```json { "channelIds": [ "UCX6OQ3DkcsbYNE6H8uQQuVA", "UCsBjURrPoezykLs9EqgamOA" ], "keywords": [ "ai", "automation", "startup", "marketing", "software", "developer", "business", "launch" ], "maxResults": 20, "minScore": 0, "includeSummary": true } ```` # Actor output Schema ## `results` (type: `string`): Dataset rows containing scored public YouTube videos from channel RSS feeds. ## `summary` (type: `string`): Summary JSON stored in the default key-value store under SUMMARY. # 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 = { "channelIds": [ "UCX6OQ3DkcsbYNE6H8uQQuVA", "UCsBjURrPoezykLs9EqgamOA" ], "keywords": [ "ai", "automation", "startup", "marketing", "software", "developer", "business", "launch" ] }; // Run the Actor and wait for it to finish const run = await client.actor("viniman27/youtube-channel-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "channelIds": [ "UCX6OQ3DkcsbYNE6H8uQQuVA", "UCsBjURrPoezykLs9EqgamOA", ], "keywords": [ "ai", "automation", "startup", "marketing", "software", "developer", "business", "launch", ], } # Run the Actor and wait for it to finish run = client.actor("viniman27/youtube-channel-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "channelIds": [ "UCX6OQ3DkcsbYNE6H8uQQuVA", "UCsBjURrPoezykLs9EqgamOA" ], "keywords": [ "ai", "automation", "startup", "marketing", "software", "developer", "business", "launch" ] }' | apify call viniman27/youtube-channel-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=viniman27/youtube-channel-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Channel Intelligence", "description": "Monitor public YouTube channel RSS feeds and enrich recent videos for trend scouting, lead discovery, creator research, and content intelligence.", "version": "0.1", "x-build-id": "tcWq7YmtnTS9eiAew" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/viniman27~youtube-channel-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-viniman27-youtube-channel-intelligence", "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/viniman27~youtube-channel-intelligence/runs": { "post": { "operationId": "runs-sync-viniman27-youtube-channel-intelligence", "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/viniman27~youtube-channel-intelligence/run-sync": { "post": { "operationId": "run-sync-viniman27-youtube-channel-intelligence", "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", "properties": { "channelIds": { "title": "Channel IDs", "type": "array", "description": "Public YouTube channel IDs to monitor via RSS.", "items": { "type": "string" } }, "feedUrls": { "title": "Feed URLs", "type": "array", "description": "Optional full YouTube RSS feed URLs. Use when channel ID is already embedded in a feed URL.", "items": { "type": "string" } }, "keywords": { "title": "Commercial keywords", "type": "array", "description": "Keywords used to tag and score videos.", "items": { "type": "string" } }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of enriched videos to output. Keep small for cheap runs.", "default": 20 }, "minScore": { "title": "Min score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only output videos with opportunity_score greater than or equal to this value.", "default": 0 }, "includeSummary": { "title": "Include summary", "type": "boolean", "description": "Store a SUMMARY record in the default key-value store.", "default": true } } }, "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 } } } } } } } } } } ```