# 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 '' with your token const client = new ApifyClient({ 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 '' with your token. client = ApifyClient("") # 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 " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Transcript Scraper — Subtitles & Captions for RAG", "description": "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.", "version": "0.1", "x-build-id": "vy3Wd5C456gXxHRS1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ahampton83~youtube-transcript-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ahampton83-youtube-transcript-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ahampton83~youtube-transcript-scraper/runs": { "post": { "operationId": "runs-sync-ahampton83-youtube-transcript-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ahampton83~youtube-transcript-scraper/run-sync": { "post": { "operationId": "run-sync-ahampton83-youtube-transcript-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "videoUrls": { "title": "Video URLs", "type": "array", "description": "One or more YouTube video URLs to fetch transcripts from.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "channelUrl": { "title": "Channel URL", "type": "string", "description": "YouTube channel URL to fetch recent video transcripts from. Use instead of videoUrls for channel mode.", "default": "" }, "maxVideos": { "title": "Max videos from channel", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of videos to process from a channel.", "default": 10 }, "includeTimestamps": { "title": "Include timestamps", "type": "boolean", "description": "Include timing data (start, duration) in output segments.", "default": true }, "language": { "title": "Preferred language", "type": "string", "description": "Preferred language code for transcripts (e.g., 'en', 'es', 'fr'). Falls back to first available.", "default": "en" }, "format": { "title": "Output format", "enum": [ "text", "segments", "both" ], "type": "string", "description": "Return plain text, timestamped segments, or both.", "default": "both" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```