# YouTube Transcript Pro - Office Edition (`vigilant_arboretum/youtube-transcript-pro`) Actor

Bulk YouTube transcript extractor with job tracking, timestamps, and stats.

- **URL**: https://apify.com/vigilant\_arboretum/youtube-transcript-pro.md
- **Developed by:** [Aman Bhawsar](https://apify.com/vigilant_arboretum) (community)
- **Categories:** Videos
- **Stats:** 7 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 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 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 Transcript Pro — Office Edition

Bulk YouTube transcript & subtitle extractor for content teams, research, and
AI training datasets.

### Features

- Bulk URL processing (watch, youtu.be, shorts, embed)
- 100+ languages
- Optional timestamped output (`[mm:ss] text`)
- Job tracking — every run gets a unique `job_id` and optional `job_label`
- Per-video stats: line count, word count, duration
- Run summary saved to key-value store as `JOB_SUMMARY`

### Run limits (Office edition)

To keep runs fast and lightweight, this edition caps each execution:

- **Max 5 videos per run** — extra URLs are trimmed with a log notice.
- **Max 3 minutes runtime** — any video beyond this is skipped and reported
  in the summary as `stopped_by_timeout: true`.

For larger bulk jobs, split the input across multiple runs.

### Input

| Field | Type | Description |
|---|---|---|
| `urls` | array (required) | YouTube video URLs |
| `language` | string | Preferred subtitle language code (default: `en`) |
| `jobLabel` | string | Optional label for this batch (team/project name) |
| `includeTimestamps` | boolean | Prefix each line with `[mm:ss]` |

### Output (per video)

```json
{
  "job_id": "JOB-20260405XXXXXX-AB12",
  "job_label": "marketing-q2",
  "video_id": "dQw4w9WgXcQ",
  "url": "https://...",
  "language": "en",
  "line_count": 142,
  "word_count": 980,
  "duration_sec": 213,
  "extracted_at": "2026-04-05T...Z",
  "transcript": "...",
  "lines": ["..."],
  "raw": [...]
}
```

### Run Summary

After every run, a `JOB_SUMMARY` record is written to the default key-value
store containing totals, success/failure counts, and timing.

# Actor input Schema

## `urls` (type: `array`):

List of YouTube video URLs to extract transcripts from (max 5 per run).

## `language` (type: `string`):

Preferred transcript language code (e.g. en, hi, es, fr).

## `includeTimestamps` (type: `boolean`):

Add \[MM:SS] timestamps before each transcript line.

## `jobLabel` (type: `string`):

Optional label to tag this job for easy identification.

## Actor input object example

```json
{
  "urls": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "language": "en",
  "includeTimestamps": false
}
```

# 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 = {
    "urls": [
        "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
    ],
    "language": "en"
};

// Run the Actor and wait for it to finish
const run = await client.actor("vigilant_arboretum/youtube-transcript-pro").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 = {
    "urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "language": "en",
}

# Run the Actor and wait for it to finish
run = client.actor("vigilant_arboretum/youtube-transcript-pro").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 '{
  "urls": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "language": "en"
}' |
apify call vigilant_arboretum/youtube-transcript-pro --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=vigilant_arboretum/youtube-transcript-pro",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Y8xHMa6nGH46ph3h1/builds/UQZcrH8jabHes50LB/openapi.json