# YouTube Search Scraper (`datacortex/youtube-search-scraper`) Actor

Search YouTube and export video title, URL, channel, views, duration, thumbnail, and publish time. Filters for date, type, duration, sort, HD, live, and captions.

- **URL**: https://apify.com/datacortex/youtube-search-scraper.md
- **Developed by:** [datacortex](https://apify.com/datacortex) (community)
- **Categories:** Social media, Videos
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 search 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/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 Search Scraper

Search YouTube and download structured results: **title, URL, video ID, channel, views, duration, thumbnail, and publish time**.

Built for Apify Console, API, MCP agents, and integrations (Make, Zapier, n8n). One dataset row per result — ready for CSV, Excel, or JSON export.

### What you get

| Field | Example |
| --- | --- |
| `title` | How to Make a Website in 10 Minutes |
| `url` | https://www.youtube.com/watch?v=LK9XuImr8Xg |
| `videoId` | LK9XuImr8Xg |
| `channelName` | Web Dev Simplified |
| `channelUrl` | https://www.youtube.com/channel/UC… |
| `views` | 1200000 |
| `duration` | 10:32 |
| `publishedTime` | 2 weeks ago |
| `thumbnailUrl` | https://i.ytimg.com/vi/…/hq720.jpg |

Standard search returns up to **20 results per query**. Turn on **Deep search** for up to **700**.

### How to run

1. Open the Actor in Apify Console.
2. Enter one search term per line under **Search queries**.
3. Optional: set country, upload date, type, duration, sort, HD / live / captions.
4. Click **Start**. Open the **Output** tab when the run finishes.

#### Example input

```json
{
  "queries": ["how to make a website"],
  "deep": false,
  "maxResults": 20,
  "sortBy": "relevance"
}
```

#### API

```bash
curl -X POST "https://api.apify.com/v2/acts/datacortex~youtube-search-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["how to make a website"],"deep":false}'
```

Replace `YOUR_TOKEN` with an Apify API token.

### Use with MCP / agents

This is a normal Apify Actor. Agents call it through [Apify MCP](https://docs.apify.com/integrations/mcp) — you do not run a separate MCP process.

Pin this Actor as a tool (after it is public):

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=datacortex/youtube-search-scraper"
    }
  }
}
```

The agent should `fetch-actor-details` on `datacortex/youtube-search-scraper`, then run it with the same JSON as **Example input** above. Running Actors requires an Apify token (OAuth in the client, or `Authorization: Bearer <APIFY_TOKEN>`).

### Pricing

**$0.50 per 1,000 results** + $0.001 per run.

| Event | When it fires | Price |
| --- | --- | --- |
| `apify-actor-start` | Once when the run starts | **$0.001** |
| `apify-default-dataset-item` | Once per dataset row (usually one video) | **$0.0005** ($0.50 / 1,000) |

| Job | Rows | You pay |
| --- | --- | --- |
| 1 query, standard (~20 videos) | 20 | $0.001 + $0.010 = **$0.011** |
| 10 queries, standard | ~200 | $0.001 + $0.100 = **$0.101** |
| 1 query, deep (~700 videos) | 700 | $0.001 + $0.350 = **$0.351** |

Set a **max total charge per run** so a deep search cannot overrun budget. The Actor stops when that limit is reached.

### Input reference

| Field | Required | Default | Notes |
| --- | --- | --- | --- |
| `queries` | yes | — | One term per line, max 1,000 |
| `deep` | no | `false` | `true` → up to 700 results / query |
| `maxResults` | no | all | Hard cap across every query |
| `geoLocation` | no | — | e.g. `United States` |
| `uploadDate` | no | — | `last_hour`, `today`, `this_week`, `this_month`, `this_year` |
| `resultType` | no | — | `video`, `channel`, `playlist`, `movie` |
| `duration` | no | — | `<4`, `4-20`, `>20` |
| `sortBy` | no | `relevance` | `relevance`, `upload_date`, `view_count`, `rating` |
| `hd` / `live` / `subtitles` | no | `false` | YouTube quality filters |

### Limitations

- This Actor searches YouTube. It does **not** download video files, transcripts, or comments.
- View counts and “published X ago” are what YouTube shows on the search page, not live analytics.
- Failed queries write one `type: "error"` row so you can see which term failed.

### Local development

```bash
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
apify run --input-file=apify_input.json --purge
```

### Changelog

See [CHANGELOG.md](CHANGELOG.md).

# Actor input Schema

## `queries` (type: `array`):

One YouTube search term per line. Example: `how to make a website`.

## `deep` (type: `boolean`):

Off: up to 20 results per query. On: up to 700 results per query. Deep search returns more rows, so dataset charges are higher.

## `maxResults` (type: `integer`):

Stop after this many dataset rows across all queries. Leave empty to keep every result returned.

## `geoLocation` (type: `string`):

Country to search from. Examples: `United States`, `India`, `United Kingdom`.

## `uploadDate` (type: `string`):

Only keep results uploaded in this window.

## `resultType` (type: `string`):

Restrict results to one YouTube content type.

## `duration` (type: `string`):

Video length filter, in minutes.

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

YouTube sort order. Default is relevance.

## `hd` (type: `boolean`):

Only return high-definition videos.

## `live` (type: `boolean`):

Only return live streams.

## `subtitles` (type: `boolean`):

Only return videos that have captions / closed captions.

## Actor input object example

```json
{
  "queries": [
    "how to make a website"
  ],
  "deep": false,
  "sortBy": "relevance",
  "hd": false,
  "live": false,
  "subtitles": false
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset of flattened YouTube search results.

# 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 = {
    "queries": [
        "how to make a website"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("datacortex/youtube-search-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 = { "queries": ["how to make a website"] }

# Run the Actor and wait for it to finish
run = client.actor("datacortex/youtube-search-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 '{
  "queries": [
    "how to make a website"
  ]
}' |
apify call datacortex/youtube-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datacortex/youtube-search-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/Cjqo6HulodVreYiCr/builds/QfF4sS0pbgHqKwQzH/openapi.json