# Youtube Comments Extractor (`agenscrape/youtube-comments-extractor`) Actor Extract YouTube video comments with ease. Get comment text, author info, likes, reply counts, and timestamps. Supports video URLs and IDs. Extract unlimited comments. Perfect for sentiment analysis, market research, and content monitoring. - **URL**: https://apify.com/agenscrape/youtube-comments-extractor.md - **Developed by:** [Agenscrape](https://apify.com/agenscrape) (community) - **Categories:** Videos, Social media, Developer tools - **Stats:** 3 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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.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 Comments Extractor Extract comments from any YouTube video quickly and efficiently. Get all the data you need including comment text, author information, engagement metrics, and timestamps. ### Features - **Fast extraction** - Get thousands of comments in minutes - **Full comment data** - Text, author, likes, reply count, timestamps - **Flexible input** - Accepts video ID or full YouTube URL - **Multiple URL formats** - youtube.com, youtu.be, shorts, embed links - **Unlimited** - Extract all comments from any video ### Input | Field | Type | Description | |-------|------|-------------| | videoId | string | YouTube video ID or full URL | | maxResults | integer | Maximum comments to extract. Set 0 for all comments (default: 0) | #### Supported URL Formats - Video ID: `dQw4w9WgXcQ` - Standard: `https://www.youtube.com/watch?v=dQw4w9WgXcQ` - Short URL: `https://youtu.be/dQw4w9WgXcQ` - Shorts: `https://www.youtube.com/shorts/dQw4w9WgXcQ` - Embed: `https://www.youtube.com/embed/dQw4w9WgXcQ` ### Output Each comment includes: | Field | Description | |-------|-------------| | commentId | Unique comment identifier | | videoId | Source video ID | | text | Comment content | | author | Author display name | | authorChannelUrl | Link to author's channel | | authorProfileImage | Author's profile picture URL | | likes | Number of likes | | replyCount | Number of replies | | publishedAt | When comment was posted | | updatedAt | Last edit timestamp | ### Example Output ```json { "commentId": "UgxK2...", "videoId": "dQw4w9WgXcQ", "text": "This song is timeless!", "author": "MusicFan123", "authorChannelUrl": "http://www.youtube.com/@MusicFan123", "authorProfileImage": "https://yt3.ggpht.com/...", "likes": 1542, "replyCount": 23, "publishedAt": "2024-01-15T10:30:00Z", "updatedAt": "2024-01-15T10:30:00Z" } ```` ### Use Cases - **Sentiment analysis** - Analyze audience reactions - **Market research** - Understand customer opinions - **Content analysis** - Study engagement patterns - **Competitor research** - Monitor competitor video feedback - **Trend detection** - Identify popular topics in comments # Actor input Schema ## `videoId` (type: `string`): YouTube video ID or full URL. Supports formats: video ID (e.g., dQw4w9WgXcQ), youtube.com/watch?v=..., youtu.be/..., youtube.com/shorts/... ## `maxResults` (type: `integer`): Maximum number of comments to extract. Set 0 for all comments. Free users are limited to 100 results. ## Actor input object example ```json { "videoId": "dQw4w9WgXcQ", "maxResults": 100 } ``` # 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 = { "videoId": "dQw4w9WgXcQ", "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("agenscrape/youtube-comments-extractor").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 = { "videoId": "dQw4w9WgXcQ", "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("agenscrape/youtube-comments-extractor").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 '{ "videoId": "dQw4w9WgXcQ", "maxResults": 100 }' | apify call agenscrape/youtube-comments-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agenscrape/youtube-comments-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Comments Extractor", "description": "Extract YouTube video comments with ease. Get comment text, author info, likes, reply counts, and timestamps. Supports video URLs and IDs. Extract unlimited comments. Perfect for sentiment analysis, market research, and content monitoring.", "version": "1.0", "x-build-id": "S9wBChv5QJkaEAz8X" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agenscrape~youtube-comments-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agenscrape-youtube-comments-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agenscrape~youtube-comments-extractor/runs": { "post": { "operationId": "runs-sync-agenscrape-youtube-comments-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agenscrape~youtube-comments-extractor/run-sync": { "post": { "operationId": "run-sync-agenscrape-youtube-comments-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "videoId" ], "properties": { "videoId": { "title": "Video ID or URL", "type": "string", "description": "YouTube video ID or full URL. Supports formats: video ID (e.g., dQw4w9WgXcQ), youtube.com/watch?v=..., youtu.be/..., youtube.com/shorts/..." }, "maxResults": { "title": "Maximum Results", "minimum": 0, "type": "integer", "description": "Maximum number of comments to extract. Set 0 for all comments. Free users are limited to 100 results.", "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 } } } } } } } } } } ```