# YouTube Comments Scraper (`technicaldost/youtube-comments-scraper`) Actor Scrape comments from any YouTube video: text, author, likes, replies, pinned/hearted status. For social listening, sentiment analysis and audience research. - **URL**: https://apify.com/technicaldost/youtube-comments-scraper.md - **Developed by:** [Technical Dost Solutions](https://apify.com/technicaldost) (community) - **Categories:** Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Comments Scraper Export public YouTube comments as clean, analysis-ready records. This Actor is designed for social listening, audience research, brand monitoring, sentiment analysis, creator research, and community discovery. It uses YouTube's public watch pages and InnerTube web API. No YouTube Data API key, paid proxy, or paid third-party data source is required. ### What it does - Scrapes top or newest comments from one or more public YouTube videos. - Paginates through YouTube comments up to the requested per-video limit. - Returns comment text, author and channel link, relative publish time, likes, replies, and pinned or creator-hearted status. - Supports both YouTube's current comment entity payloads and the legacy inline comment renderer. - Continues processing when one video fails and handles disabled comments without failing the run. ### Input ```json { "videoUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "maxCommentsPerVideo": 100, "sortBy": "top" } ```` | Field | Type | Required | Description | | --- | --- | --- | --- | | `videoUrls` | array of strings | Yes | Public YouTube watch, short, live, embed, or `youtu.be` video URLs. | | `maxCommentsPerVideo` | integer | No | Comments per video, from 1 to 500. Defaults to 100. | | `sortBy` | string | No | `top` or `newest`. Defaults to `top`. | The limit applies to top-level comments. Reply counts are included when YouTube exposes them, but replies are not emitted as separate records. ### Output Each dataset item represents one comment: ```json { "videoId": "dQw4w9WgXcQ", "videoUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "commentId": "UgzExampleCommentId", "text": "Example comment text", "author": "@ExampleAuthor", "authorChannelUrl": "https://www.youtube.com/@ExampleAuthor", "publishedTimeText": "2 days ago", "likeCountText": "1.2K", "likeCount": 1200, "replyCount": 8, "isPinned": false, "isHearted": true } ``` `likeCount` and `replyCount` are `null` when YouTube does not expose a parseable count. `isHearted` is `false` when a creator heart cannot be detected. ### Cost and data source The Actor uses only public YouTube web data and native HTTP requests. Each stored comment triggers the `result` pay-per-event charge when that event is configured on Apify. # Actor input Schema ## `videoUrls` (type: `array`): Public YouTube video URLs whose comments should be scraped. ## `maxCommentsPerVideo` (type: `integer`): Maximum number of top-level comments to return for each video. ## `sortBy` (type: `string`): Return YouTube's top comments or newest comments first. ## Actor input object example ```json { "videoUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "maxCommentsPerVideo": 100, "sortBy": "top" } ``` # 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 = { "videoUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ] }; // Run the Actor and wait for it to finish const run = await client.actor("technicaldost/youtube-comments-scraper").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 = { "videoUrls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"] } # Run the Actor and wait for it to finish run = client.actor("technicaldost/youtube-comments-scraper").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 '{ "videoUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ] }' | apify call technicaldost/youtube-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=technicaldost/youtube-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Comments Scraper", "description": "Scrape comments from any YouTube video: text, author, likes, replies, pinned/hearted status. For social listening, sentiment analysis and audience research.", "version": "0.1", "x-build-id": "pZ0mOfmjydiK7CIX7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/technicaldost~youtube-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-technicaldost-youtube-comments-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/technicaldost~youtube-comments-scraper/runs": { "post": { "operationId": "runs-sync-technicaldost-youtube-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/technicaldost~youtube-comments-scraper/run-sync": { "post": { "operationId": "run-sync-technicaldost-youtube-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "videoUrls" ], "properties": { "videoUrls": { "title": "YouTube video URLs", "type": "array", "description": "Public YouTube video URLs whose comments should be scraped.", "items": { "type": "string" } }, "maxCommentsPerVideo": { "title": "Maximum comments per video", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of top-level comments to return for each video.", "default": 100 }, "sortBy": { "title": "Comment sorting", "enum": [ "top", "newest" ], "type": "string", "description": "Return YouTube's top comments or newest comments first.", "default": "top" } } }, "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 } } } } } } } } } } ```