# YouTube Channel Transcripts - whole channel to RAG (`jamhimself/youtube-channel-transcripts`) Actor Give it a YouTube channel and get every video's transcript as RAG-ready chunks in one run. Lists the channel, fetches all captions (JSON, text, SRT, VTT, or chunked). No API key, pay per transcript. - **URL**: https://apify.com/jamhimself/youtube-channel-transcripts.md - **Developed by:** [Jaime Martinez](https://apify.com/jamhimself) (community) - **Categories:** Developer tools, Videos, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $7.50 / 1,000 transcripts 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 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 Channel Transcripts — whole channel to RAG in one run YouTube Channel Transcripts for developers and AI pipelines — give it a **channel** and get **every video's transcript** back as RAG-ready chunks (or plain text, SRT, VTT) in a single run. No API key, no quotas, no chaining tools together. Point it at a channel, get a knowledge base out. This does in one step what normally takes two: it **lists the whole channel**, then **fetches every caption track** through a hosted residential-proxy + uptime layer that handles YouTube's 2026 PoToken wall — the thing that makes free libraries return nothing. ### Why this exists Building RAG over a creator's catalog means: enumerate every video in the channel, then pull each transcript, then chunk it for embeddings. That's a multi-step pipeline most people stitch together by hand. This actor is the whole pipeline — **channel in → chunked transcripts out** — so an AI agent or a LangChain/LlamaIndex job can ingest an entire channel with one call. ### What you get (per video) - `channelTitle`, `videoId`, `url`, `title`, `publishedText`, `viewCount`, `durationSeconds` - `text` — the full transcript as clean text - `chunks` — RAG-ready overlapping chunks, each with `startSeconds`, `endSeconds`, and a clickable `deepLink` into the video at that timestamp - Optional `segments` (timestamped), `srt`, `vtt` ### Input | Field | Type | Description | |---|---|---| | `channels` | array | **Required.** @handles, channel URLs, or UC… ids. | | `maxVideosPerChannel` | integer | Newest N videos per channel (default 50). | | `languages` | array | Preferred caption languages (default `["en"]`). | | `ragChunking` | boolean | Emit RAG chunks (default **true**). | | `chunkMaxChars` / `chunkOverlapChars` | integer | Chunk sizing. | ### Use cases - **RAG / LLM ingestion** — turn a creator's entire catalog into an embeddable knowledge base in one call - **Agent workflows** — "summarize everything channel X has said about Y" - **Research & monitoring** — full-text search across a channel's spoken content - **Dataset building** — transcript corpora per channel ### Pricing **Pay per transcript delivered.** Listing the channel is free; videos with no captions or that fail are skipped and never billed. No subscription, no API key. See the **Pricing** tab for the current rate. ### Related actors - **[YouTube Transcript Scraper](https://apify.com/jamhimself/youtube-transcript-extractor)** — transcripts for specific video URLs - **[YouTube Channel Videos Scraper](https://apify.com/jamhimself/youtube-channel-videos)** — just the video list (no transcripts) - **[YouTube Comments Scraper](https://apify.com/jamhimself/youtube-comments-scraper)** — audience data ### FAQ - **Do I need a YouTube API key?** No — no key, no OAuth, no quota. - **Big channels?** Set `maxVideosPerChannel`; it pages through and transcribes the newest N. - **No-caption videos?** Skipped for free; you only pay for transcripts actually delivered. - **Legal?** It accesses publicly available data. You are responsible for complying with YouTube's Terms of Service and applicable law in your use of the output. # Actor input Schema ## `channels` (type: `array`): YouTube channels — @handles (e.g. @mkbhd), channel URLs, or UC… channel IDs. The actor lists every video and returns each one's transcript. ## `maxVideosPerChannel` (type: `integer`): How many of the channel's newest videos to transcribe. ## `languages` (type: `array`): Caption language codes in order of preference (e.g. ["en", "es"]). Falls back to English, then the first available track. ## `preferManual` (type: `boolean`): Prefer human-uploaded captions over auto-generated (ASR) when both exist. ## `ragChunking` (type: `boolean`): Split each transcript into overlapping chunks with timestamps + deep links — ready for embedding pipelines (LangChain, LlamaIndex, vector DBs). ## `chunkMaxChars` (type: `integer`): Maximum characters per RAG chunk. ## `chunkOverlapChars` (type: `integer`): Approximate character overlap between consecutive chunks. ## `includePlainText` (type: `boolean`): Include the full transcript as one clean text string per video. ## `includeSegments` (type: `boolean`): Include the raw {start, duration, text} segment array per video. ## `includeSrt` (type: `boolean`): Include a SubRip (.srt) subtitle string per video. ## `includeVtt` (type: `boolean`): Include a WebVTT (.vtt) subtitle string per video. ## `concurrency` (type: `integer`): How many videos to transcribe in parallel (1-10). ## `proxyCountryCode` (type: `string`): Optional two-letter country code for proxies. ## Actor input object example ```json { "channels": [ "@mkbhd" ], "maxVideosPerChannel": 50, "languages": [ "en" ], "preferManual": true, "ragChunking": true, "chunkMaxChars": 1500, "chunkOverlapChars": 200, "includePlainText": true, "includeSegments": false, "includeSrt": false, "includeVtt": false, "concurrency": 5 } ```` # 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 = { "channels": [ "@mkbhd" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jamhimself/youtube-channel-transcripts").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 = { "channels": ["@mkbhd"] } # Run the Actor and wait for it to finish run = client.actor("jamhimself/youtube-channel-transcripts").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 '{ "channels": [ "@mkbhd" ] }' | apify call jamhimself/youtube-channel-transcripts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jamhimself/youtube-channel-transcripts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Channel Transcripts - whole channel to RAG", "description": "Give it a YouTube channel and get every video's transcript as RAG-ready chunks in one run. Lists the channel, fetches all captions (JSON, text, SRT, VTT, or chunked). No API key, pay per transcript.", "version": "1.0", "x-build-id": "dCtpYHVDfjggkr7Fn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jamhimself~youtube-channel-transcripts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jamhimself-youtube-channel-transcripts", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jamhimself~youtube-channel-transcripts/runs": { "post": { "operationId": "runs-sync-jamhimself-youtube-channel-transcripts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jamhimself~youtube-channel-transcripts/run-sync": { "post": { "operationId": "run-sync-jamhimself-youtube-channel-transcripts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "channels" ], "properties": { "channels": { "title": "Channels", "type": "array", "description": "YouTube channels — @handles (e.g. @mkbhd), channel URLs, or UC… channel IDs. The actor lists every video and returns each one's transcript.", "items": { "type": "string" } }, "maxVideosPerChannel": { "title": "Max videos per channel", "minimum": 1, "maximum": 2000, "type": "integer", "description": "How many of the channel's newest videos to transcribe.", "default": 50 }, "languages": { "title": "Preferred languages", "type": "array", "description": "Caption language codes in order of preference (e.g. [\"en\", \"es\"]). Falls back to English, then the first available track.", "default": [ "en" ], "items": { "type": "string" } }, "preferManual": { "title": "Prefer manual captions", "type": "boolean", "description": "Prefer human-uploaded captions over auto-generated (ASR) when both exist.", "default": true }, "ragChunking": { "title": "RAG-ready chunks", "type": "boolean", "description": "Split each transcript into overlapping chunks with timestamps + deep links — ready for embedding pipelines (LangChain, LlamaIndex, vector DBs).", "default": true }, "chunkMaxChars": { "title": "Chunk size (characters)", "minimum": 200, "maximum": 20000, "type": "integer", "description": "Maximum characters per RAG chunk.", "default": 1500 }, "chunkOverlapChars": { "title": "Chunk overlap (characters)", "minimum": 0, "maximum": 5000, "type": "integer", "description": "Approximate character overlap between consecutive chunks.", "default": 200 }, "includePlainText": { "title": "Include plain text", "type": "boolean", "description": "Include the full transcript as one clean text string per video.", "default": true }, "includeSegments": { "title": "Include timestamped segments", "type": "boolean", "description": "Include the raw {start, duration, text} segment array per video.", "default": false }, "includeSrt": { "title": "Include SRT", "type": "boolean", "description": "Include a SubRip (.srt) subtitle string per video.", "default": false }, "includeVtt": { "title": "Include VTT", "type": "boolean", "description": "Include a WebVTT (.vtt) subtitle string per video.", "default": false }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many videos to transcribe in parallel (1-10).", "default": 5 }, "proxyCountryCode": { "title": "Proxy country", "type": "string", "description": "Optional two-letter country code for proxies." } } }, "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 } } } } } } } } } } ```