# YouTube Transcript Scraper — Subtitles & Captions for RAG (`ahampton83/youtube-transcript-scraper`) Actor

Fetch YouTube video transcripts and subtitles as clean text or timestamped segments. Perfect for RAG pipelines, content analysis, and AI agents. Use via Apify Console/API or connect as an MCP server for Claude, Cursor, and other AI agents.

- **URL**: https://apify.com/ahampton83/youtube-transcript-scraper.md
- **Developed by:** [Aaron Hampton](https://apify.com/ahampton83) (community)
- **Categories:** SEO tools, News, MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 trends queries

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/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 Scraper — Subtitles & Captions for RAG

Fetch YouTube video transcripts and subtitles as clean text or timestamped segments. Perfect for RAG pipelines, content analysis, accessibility tools, and AI agents.

### Features

- **Single & batch mode** — fetch one video's transcript or walk an entire channel
- **Full-text search** — search across multiple video transcripts for specific topics
- **Language selection** — prefer a specific language, fall back to auto-generated captions
- **Timestamped segments** — get clean `{ start, duration, text }` segments or plain text
- **Dual-mode** — run as a normal Apify Actor OR connect as an MCP server for Claude, Cursor, and other AI agents
- **No browser required** — uses YouTube's internal timedtext API directly

### Use Cases

- **RAG pipelines** — feed transcripts into vector databases for Q\&A over video content
- **Content analysis** — extract key topics, sentiment, or keywords from video transcripts
- **Accessibility** — get subtitles for videos that lack proper captioning
- **AI agents** — let Claude/Cursor read video content via MCP tools
- **Research** — search across many video transcripts to find specific information

### Input (Normal Actor Mode)

| Field | Type | Description |
|-------|------|-------------|
| `videoUrls` | array | YouTube video URLs to fetch transcripts from |
| `channelUrl` | string | Channel URL to fetch recent video transcripts |
| `maxVideos` | integer | Max videos from channel (default 10, max 50) |
| `includeTimestamps` | boolean | Include timing data (default true) |
| `language` | string | Preferred language code (default "en") |
| `format` | enum | "text", "segments", or "both" (default "both") |

### Output

```json
{
  "videoId": "dQw4w9gWgXc",
  "videoUrl": "https://youtube.com/watch?v=dQw4w9gWgXc",
  "title": "Video Title",
  "language": "en",
  "isAutoGenerated": false,
  "text": "Full plain text transcript...",
  "segments": [
    { "start": 0.0, "duration": 3.5, "text": "First segment" },
    { "start": 3.5, "duration": 2.1, "text": "Second segment" }
  ],
  "fetchedAt": "2026-07-04T00:00:00.000Z"
}
```

### MCP Tools (Standby Mode)

#### `get_transcript`

Fetch a single video's transcript.

```json
{
  "videoUrl": "https://www.youtube.com/watch?v=dQw4w9gWgXc",
  "language": "en",
  "format": "both"
}
```

#### `get_channel_transcripts`

Batch-fetch transcripts for a channel's recent videos.

```json
{
  "channelUrl": "https://www.youtube.com/@channelname",
  "maxVideos": 10,
  "language": "en"
}
```

#### `search_transcripts`

Search across multiple video transcripts for a query.

```json
{
  "query": "machine learning",
  "videoUrls": [
    "https://www.youtube.com/watch?v=abc",
    "https://www.youtube.com/watch?v=def"
  ]
}
```

### Pricing (Pay Per Event)

| Event | Price | Free Tier |
|-------|-------|-----------|
| Actor start | $0.00005 | — |
| Transcript fetched | $0.005 | First 3 free per run/tool call |
| MCP tool call | $0.01 | — |

Tiered discounts available (Bronze → Diamond).

### Technical Approach

1. Fetch the YouTube watch page HTML
2. Extract `ytInitialPlayerResponse` JSON containing caption track metadata
3. Select the best caption track (manual > ASR, preferred language > fallback)
4. Fetch the timedtext XML from the caption track's `baseUrl`
5. Parse XML into clean segments with timestamps
6. Fallback to direct timedtext API if watch page scraping fails

### Development

```bash
npm install      # Install dependencies
npm run build    # Compile TypeScript
npm test         # Run tests
npm run start:dev  # Run in dev mode
```

### Author

**Aaron Hampton**

### License

ISC

# Actor input Schema

## `videoUrls` (type: `array`):

One or more YouTube video URLs to fetch transcripts from.

## `channelUrl` (type: `string`):

YouTube channel URL to fetch recent video transcripts from. Use instead of videoUrls for channel mode.

## `maxVideos` (type: `integer`):

Maximum number of videos to process from a channel.

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

Include timing data (start, duration) in output segments.

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

Preferred language code for transcripts (e.g., 'en', 'es', 'fr'). Falls back to first available.

## `format` (type: `string`):

Return plain text, timestamped segments, or both.

## Actor input object example

```json
{
  "videoUrls": [
    {
      "url": "https://www.youtube.com/watch?v=dQw4w9gWgXc"
    }
  ],
  "channelUrl": "",
  "maxVideos": 10,
  "includeTimestamps": true,
  "language": "en",
  "format": "both"
}
```

# 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 = {
    "videoUrls": [
        {
            "url": "https://www.youtube.com/watch?v=dQw4w9gWgXc"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("ahampton83/youtube-transcript-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 = { "videoUrls": [{ "url": "https://www.youtube.com/watch?v=dQw4w9gWgXc" }] }

# Run the Actor and wait for it to finish
run = client.actor("ahampton83/youtube-transcript-scraper").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 '{
  "videoUrls": [
    {
      "url": "https://www.youtube.com/watch?v=dQw4w9gWgXc"
    }
  ]
}' |
apify call ahampton83/youtube-transcript-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=ahampton83/youtube-transcript-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/J2osjrXzaL3bwdJc7/builds/vy3Wd5C456gXxHRS1/openapi.json