# YouTube Transcript Tool Server (MCP-compatible) (`verifiable_clamp/youtube-transcript-tools`) Actor Fetch YouTube video transcripts + metadata via tool-style invocations using public endpoints (no API key). Tools: video\_transcript, video\_metadata, channel\_videos, playlist\_videos. - **URL**: https://apify.com/verifiable\_clamp/youtube-transcript-tools.md - **Developed by:** [Rara21](https://apify.com/verifiable_clamp) (community) - **Categories:** Videos, AI - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results 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 ## Apify YouTube Transcript Tool Server (MCP-style) An Apify Actor that exposes YouTube transcripts + metadata as a small set of tools an LLM agent can call — one Actor run = one tool call. Uses only **public endpoints**: the watch page HTML, the `timedtext` caption API, the `oEmbed` endpoint, and the channel/playlist RSS feeds. **No API key required.** ### Tools | Tool | Purpose | |---|---| | `video_transcript` | Fetch a video's caption track as timestamped segments + merged full text | | `video_metadata` | Title, author, thumbnail (via oEmbed) | | `channel_videos` | Latest videos from a channel (RSS feed) | | `playlist_videos` | Videos from a public playlist (RSS feed) | ### Input ```json { "tool": "video_transcript", "args": { "video_id": "dQw4w9WgXcQ", "language": "en", "allow_auto": true } } ```` ### Example output: `video_transcript` ```json { "video_id": "dQw4w9WgXcQ", "language": "en", "language_name": "English", "is_auto_generated": false, "segments": [ { "start_s": 0.0, "duration_s": 2.0, "text": "Hello world." }, { "start_s": 2.0, "duration_s": 1.5, "text": "Welcome to the talk." } ], "full_text": "Hello world. Welcome to the talk." } ``` If no captions are available the response is `{ video_id, not_found: true, reason: "no_transcript_available" }`. ### Example output: `channel_videos` ```json { "channel_id": "UCsomechannel", "returned": 15, "videos": [ { "video_id": "vidaaa11111", "title": "First Video", "author": "Sample Channel", "published_at": "2026-05-01T00:00:00+00:00", "watch_url": "https://www.youtube.com/watch?v=vidaaa11111" } ] } ``` ### Run locally ``` npm install npm run build apify run --input-file=./examples/transcript.json ``` ### Tests ``` npm test ``` 22 tests across `test/client.test.ts` (watch-page parser + caption picker + json3 parser + RSS parser + oEmbed + retry) and `test/tools.test.ts` (the four tools end-to-end with a mocked fetch). ### How transcript extraction works 1. Fetch `https://www.youtube.com/watch?v=` with a normal browser UA. 2. Parse the `ytInitialPlayerResponse` JSON embedded in the page. 3. Walk `captions.playerCaptionsTracklistRenderer.captionTracks[]` and pick the best match for the requested language (or fall back to the first available, optionally skipping auto-generated tracks). 4. Fetch the picked track's `baseUrl` with `&fmt=json3` to get structured `{events: [{tStartMs, dDurationMs, segs}]}` data. 5. Flatten + clean into `[{ start_s, duration_s, text }]`. Because this is a scrape of public surfaces, YouTube can break it. The actor logs the failure mode and returns `not_found` with a `reason` rather than crashing. ### Architecture ``` src/ main.ts Apify entry — reads input, dispatches to runTool tools/index.ts Single dispatcher; one async runner per tool youtube-client.ts Watch-page scraper + json3 parser + oEmbed + RSS parser types.ts Zod schemas for input + outputs test/ fixtures.ts Realistic watch HTML + transcript + RSS + oEmbed fixtures client.test.ts 16 tests on the HTTP/parsing layer tools.test.ts 6 tests on the dispatcher ``` ### License MIT # Actor input Schema ## `tool` (type: `string`): One tool per run. The Actor charges per tool call event. ## `args` (type: `object`): JSON args specific to the selected tool. See README. ## Actor input object example ```json { "tool": "video_transcript", "args": { "video_id": "dQw4w9WgXcQ", "language": "en" } } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("verifiable_clamp/youtube-transcript-tools").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 = {} # Run the Actor and wait for it to finish run = client.actor("verifiable_clamp/youtube-transcript-tools").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 '{}' | apify call verifiable_clamp/youtube-transcript-tools --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=verifiable_clamp/youtube-transcript-tools", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Transcript Tool Server (MCP-compatible)", "description": "Fetch YouTube video transcripts + metadata via tool-style invocations using public endpoints (no API key). Tools: video_transcript, video_metadata, channel_videos, playlist_videos.", "version": "0.1", "x-build-id": "tQZRaMW9n94tDtfFP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/verifiable_clamp~youtube-transcript-tools/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-verifiable_clamp-youtube-transcript-tools", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/verifiable_clamp~youtube-transcript-tools/runs": { "post": { "operationId": "runs-sync-verifiable_clamp-youtube-transcript-tools", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/verifiable_clamp~youtube-transcript-tools/run-sync": { "post": { "operationId": "run-sync-verifiable_clamp-youtube-transcript-tools", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "tool" ], "properties": { "tool": { "title": "Tool to invoke", "enum": [ "video_transcript", "video_metadata", "channel_videos", "playlist_videos" ], "type": "string", "description": "One tool per run. The Actor charges per tool call event.", "default": "video_transcript" }, "args": { "title": "Tool arguments", "type": "object", "description": "JSON args specific to the selected tool. See README." } } }, "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 } } } } } } } } } } ```