# YouTube Comments Scraper — $0.25/1K (`scrapesignal_labs/youtube-comments-scraper`) Actor

Export public YouTube comments with authors, text, likes, replies, badges, video metadata, sorting, and keyword filters.

- **URL**: https://apify.com/scrapesignal\_labs/youtube-comments-scraper.md
- **Developed by:** [ScrapeSignal Labs](https://apify.com/scrapesignal_labs) (community)
- **Categories:** Social media, Marketing, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.25 / 1,000 youtube comments

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 rows—without requiring a YouTube Data API key.

Use it for audience research, sentiment analysis, creator monitoring, product feedback, campaign measurement, moderation support, lead signals, and AI-agent datasets.

### What you get

Each top-level comment becomes one dataset item with:

- video ID, title, channel, and direct URL
- comment ID, direct comment URL, and full visible text
- author name, channel ID, channel URL, and avatar
- displayed publication time
- parsed and original like counts
- reply count
- pinned, creator-hearted, channel-owner, and verification signals
- selected sort order and scrape timestamp

### Input example

```json
{
  "videos": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
  "sortBy": "top",
  "keywords": [],
  "minLikes": 0,
  "maxCommentsPerVideo": 100,
  "countryCode": "US",
  "languageCode": "en"
}
```

`maxCommentsPerVideo` is a hard output and price ceiling. Keyword and like filters are applied before records are saved.

### Output example

```json
{
  "videoId": "dQw4w9WgXcQ",
  "videoTitle": "Example video",
  "commentId": "Ugexample",
  "commentUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ&lc=Ugexample",
  "text": "This is still a great video.",
  "authorName": "Example viewer",
  "likes": 1200,
  "replyCount": 14,
  "isPinned": false,
  "isHearted": true
}
```

### Automation and AI agents

Use the API, OpenAPI, MCP, Python, JavaScript, CLI, webhook, or scheduling examples in the Actor's **API** tab. Store comment IDs between runs to detect new feedback, send high-like comments to Slack, or feed rows into a sentiment and topic-analysis workflow.

### Important notes

The Actor returns top-level public comments; `replyCount` shows conversation volume without billing every nested reply. Comments can be disabled, deleted, held, personalized, region-restricted, or reordered by YouTube. Visible compact counts such as `1.2K` are normalized to numbers. Respect YouTube's terms, privacy expectations, creators' rights, and applicable law.

# Actor input Schema

## `videos` (type: `array`):

Regular videos, Shorts, live replay URLs, or 11-character video IDs.

## `sortBy` (type: `string`):

Use YouTube's top-comment order or request newest comments first.

## `keywords` (type: `array`):

Optional case-insensitive terms. A comment must match at least one.

## `minLikes` (type: `integer`):

Only save comments with at least this many parsed likes.

## `maxCommentsPerVideo` (type: `integer`):

Hard output and price ceiling for each video.

## `countryCode` (type: `string`):

Two-letter YouTube market code such as US, GB, or CA.

## `languageCode` (type: `string`):

YouTube interface language such as en, es, or de.

## `maxConcurrency` (type: `integer`):

Maximum videos processed at once.

## `timeoutSeconds` (type: `integer`):

Stop waiting for an individual YouTube request after this many seconds.

## Actor input object example

```json
{
  "videos": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "sortBy": "top",
  "keywords": [],
  "minLikes": 0,
  "maxCommentsPerVideo": 100,
  "countryCode": "US",
  "languageCode": "en",
  "maxConcurrency": 2,
  "timeoutSeconds": 25
}
```

# Actor output Schema

## `dataset` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesignal_labs/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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("scrapesignal_labs/youtube-comments-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call scrapesignal_labs/youtube-comments-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesignal_labs/youtube-comments-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/e8PA8InuonUgGumDM/builds/gLf7dgqqsQ7cadeeC/openapi.json