# YouTube Metadata Scraper (`datacortex/youtube-metadata-scraper`) Actor

Look up YouTube videos by ID or URL and export title, views, likes, channel, description, duration, and upload date.

- **URL**: https://apify.com/datacortex/youtube-metadata-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 $5.00 / 1,000 video metadata

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 Metadata Scraper

Look up any public YouTube video by **ID or URL** and export **title, views, likes, channel, description, duration, thumbnail, and upload date**.

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

### What you get

| Field | Example |
| --- | --- |
| `title` | Never Gonna Give You Up |
| `url` | https://www.youtube.com/watch?v=tIgIF5lve8U |
| `videoId` | tIgIF5lve8U |
| `channelName` | Rick Astley |
| `channelUrl` | https://www.youtube.com/channel/UC… |
| `views` | 1600000000 |
| `likes` | 18000000 |
| `duration` | 3:33 |
| `publishedAt` | 2009-10-25 |
| `thumbnailUrl` | https://i.ytimg.com/vi/…/hq720.jpg |

This Actor reads **one video per input**. It does not search YouTube, download files, or pull transcripts.

### How to run

1. Open the Actor in Apify Console.
2. Paste video IDs or watch / Shorts / youtu.be URLs, one per line.
3. Optional: set a max-results cap.
4. Click **Start**. Open the **Output** tab when the run finishes.

#### Example input

```json
{
  "videoIds": [
    "tIgIF5lve8U",
    "https://www.youtube.com/watch?v=tIgIF5lve8U"
  ],
  "maxResults": 10
}
```

Duplicate IDs (including the same video as ID and URL) are fetched once.

#### API

```bash
curl -X POST "https://api.apify.com/v2/acts/datacortex~youtube-metadata-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"videoIds":["tIgIF5lve8U"]}'
```

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-metadata-scraper"
    }
  }
}
```

The agent should `fetch-actor-details` on `datacortex/youtube-metadata-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

**$5.00 per 1,000 videos** + $0.001 per run.

Each input is one vendor lookup and one dataset row. That is not the same product as a search scraper ($0.50 / 1,000), which returns many rows per query.

| Event | When it fires | Price |
| --- | --- | --- |
| `apify-actor-start` | Once when the run starts | **$0.001** |
| `apify-default-dataset-item` | Once per dataset row (one video) | **$0.005** ($5.00 / 1,000) |

| Job | Rows | You pay |
| --- | --- | --- |
| 1 video | 1 | $0.001 + $0.005 = **$0.006** |
| 10 videos | 10 | $0.001 + $0.050 = **$0.051** |
| 100 videos | 100 | $0.001 + $0.500 = **$0.501** |
| 1,000 videos | 1,000 | $0.001 + $5.000 = **$5.001** |

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

### Input reference

| Field | Required | Default | Notes |
| --- | --- | --- | --- |
| `videoIds` | yes | — | IDs or URLs, max 1,000, duplicates skipped |
| `maxResults` | no | all | Hard cap across the list |

### Limitations

- Public video metadata only. Private, deleted, members-only, and some live or geo-blocked videos return an `error` row.
- This Actor does **not** download video files, transcripts, comments, or channel subscriber lists.
- Likes and comment counts are omitted when YouTube hides them.
- Failed lookups write one `type: "error"` row so you can see which ID 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

## `videoIds` (type: `array`):

One video per line. Accepts a bare 11-character ID (`tIgIF5lve8U`) or a watch / Shorts / youtu.be / embed URL.

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

Stop after this many dataset rows. Leave empty to keep every video.

## Actor input object example

```json
{
  "videoIds": [
    "tIgIF5lve8U"
  ]
}
```

# Actor output Schema

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

Dataset of flattened YouTube video metadata.

# 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 = {
    "videoIds": [
        "tIgIF5lve8U"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("datacortex/youtube-metadata-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 = { "videoIds": ["tIgIF5lve8U"] }

# Run the Actor and wait for it to finish
run = client.actor("datacortex/youtube-metadata-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 '{
  "videoIds": [
    "tIgIF5lve8U"
  ]
}' |
apify call datacortex/youtube-metadata-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datacortex/youtube-metadata-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/ZD6UDJGWusSZ8HBcp/builds/CY74L7pXjzbQ8rgkS/openapi.json