# Twitter Video Transcript API – AI Video to Text for X (Twitter) (`apple_yang/twitter-video-transcript-api`) Actor Twitter Video Transcript API for converting video audio into accurate text using AI. Extract transcripts, spoken content, and metadata from X (Twitter) videos, tweets, and threads. Fast, reliable, and built for developers, AI agents, and automation workflows. - **URL**: https://apify.com/apple\_yang/twitter-video-transcript-api.md - **Developed by:** [APISmith](https://apify.com/apple_yang) (community) - **Categories:** Social media, Videos, AI - **Stats:** 33 total users, 20 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## 🎙️ Twitter Transcripts Scraper API Turn Twitter videos into **clean, structured transcripts** with ease. This API helps you extract **spoken content (auto-generated transcripts)** from public Twitter videos — designed for developers, data teams, and AI agents that need text, not just media. --- ### 📌 Overview The **Twitter Transcripts Scraper API** allows you to provide an Twitter video URL and receive: - 📝 **Accurate auto-generated transcript text** - ⏱️ **Timestamped segments** for precise alignment - 📊 **Rich video & author metadata** - 🎥 Direct video and audio URLs (when available) It is built to be **AI-ready, automation-friendly, and cost-effective**, making it ideal for large-scale content processing and language-focused workflows. > ⚠️ This API works with **public Twitter videos**. A valid `sessionid` may be required for stable access. --- ### 🎁 What You Can Get From This API For each Twitter video URL, the API returns: - ✅ **Full transcript text** (auto speech-to-text) - ✅ **Segmented transcript with timestamps** - ✅ Video title & thumbnail - ✅ Video, audio playback URLs - ✅ Engagement metrics (likes, comments) - ✅ Creator profile information - ✅ Error status per request (safe for automation) All data is returned in **structured JSON**, ready to feed directly into databases, AI pipelines, or downstream services. --- ### 🧩 Typical Use Cases 💡 This API is especially useful for: - 🤖 **AI agents & LLM pipelines** (speech → text ingestion) - 🧠 **Content understanding & summarization** - 🔍 **Social media content analysis** - 🎧 **Audio-to-text & subtitle generation** - 📊 **Trend and language research** - 🔁 **Batch transcription of Twitter videos** If your workflow depends on **what is being said**, not just what is being shown — this API is built for you. --- ### 💰 Cost of Usage Simple, transparent, and extremely cost-effective. - 💵 **$1.00 / 1,000 results** - 🎙️ **Audio-to-text (auto transcript) included** - 📦 Pay only for what you process — no subscriptions Perfect for both **experiments** and **large-scale AI workloads**. --- ### 📥 Input Parameters #### (1) Input Format | Field | Type | Required | Description | |-----------|--------|----------|-------------| | videoUrl | string | Yes | Public Twitter video URL | --- #### (2) Input Example ```json { "videoUrl": "https://x.com/Dell_JPN/status/1975063471155970378" } ```` *** ### 📤 Output Parameters #### (1) Output Format Description | Field | Type | Description | |---------------|---------|-------------| | url | string | Normalized Twitter video URL | | code | string | Twitter shortcode | | pk | string | Twitter internal post ID | | id | string | Combined media identifier | | title | string | Video title or hashtag | | img | string | Video thumbnail URL | | videoUrl | string | Direct video playback URL | | audioUrl | string | Direct audio playback URL | | createTime | number | Video creation timestamp | | likeCount | number | Number of likes | | commentCount | number | Number of comments | | userPk | string | Creator user ID | | userName | string | Creator username | | userFullName | string | Creator display name | | avatarUri | string | Creator avatar image URL | | text | string | Full transcript text | | segments | array | Transcript segments with timestamps | | errMsg | string | Error message (empty if success) | | timestamp | string | API response timestamp (ISO format) | *** #### (2) Output Example ```json { "url": "https://www.instagram.com/p/DTxiM0Ijqvz/", "code": "DTxiM0Ijqvz", "pk": "3814980773552761843", "id": "3814980773552761843_48143082417", "title": "#explore", "img": "https://scontent-iad3-1.cdninstagram.com/v/t51.71878-15/619803343_1676825200367728_8092852255612155538_n.jpg?stp=dst-jpg_e15_tt6&_nc_cat=1&ig_cache_key=MzgxNDk4MDc3MzU1Mjc2MTg0Mw%3D%3D.3-ccb7-5&ccb=7-5&_nc_sid=58cdad&efg=eyJ2ZW5jb2RlX3RhZyI6InhwaWRzLjY0MHgxMTM2LnNkci5DMiJ9&_nc_ohc=rQ0gvouEDUUQ7kNvwFFUA3e&_nc_oc=AdklJA8qtEC78q8uoqfq0hrHEHG_Anx14Y98_0qd-0RJTarw5mUGWP-0URYuPxKpVBw&_nc_ad=z-m&_nc_cid=0&_nc_zt=23&_nc_ht=scontent-iad3-1.cdninstagram.com&_nc_gid=1dbJ6M6MmLLlo-Jn7XlUIw&oh=00_AftPbGx5Lc3HrTwQ9YZEkCXoEVvn8Zm9VfQacfUkm8Xw1A&oe=6988A7DB", "videoUrl": "https://scontent-iad3-1.cdninstagram.com/o1/v/t2/f2/m367/AQMMUMfbkOPXkBEc4m-czR-nbdlRK3No6f05Grxopvsdq-Qg_r6pzR3qzX4VCBojSH6jpNyKgWkW-6fqtrwkdzNgO8NuKmPs4rrnfKQ.mp4?_nc_cat=104&_nc_sid=9ca052&_nc_ht=scontent-iad3-1.cdninstagram.com&_nc_ohc=b76plwG5k3UQ7kNvwESHCkA&efg=eyJ2ZW5jb2RlX3RhZyI6ImlnLXhwdmRzLmNsaXBzLmMyLUMyLmRhc2hfcjJldmV2cDktcjFnZW4ydnA5X3E4MCIsInZpZGVvX2lkIjpudWxsLCJvaWxfdXJsZ2VuX2FwcF9pZCI6OTM2NjE5NzQzMzkyNDU5LCJjbGllbnRfbmFtZSI6ImlnIiwieHB2X2Fzc2V0X2lkIjoxNzcxNTY1Njg3MTU0MjE1LCJhc3NldF9hZ2VfZGF5cyI6MTMsInZpX3VzZWNhc2VfaWQiOjEwODI3LCJkdXJhdGlvbl9zIjoxNCwiYml0cmF0ZSI6NTQwNTE1MywidXJsZ2VuX3NvdXJjZSI6Ind3dyJ9&ccb=17-1&_nc_gid=1dbJ6M6MmLLlo-Jn7XlUIw&_nc_zt=28&oh=00_Afv44NEfcLEiqZgYI0xps4ZZ93tPRuPgqh8oXzgl3VoNxg&oe=6988B5C9", "audioUrl": "https://scontent-iad3-1.cdninstagram.com/o1/v/t2/f2/m78/AQNngK6i_-6sgwETrVf-d2vgpHQhPoijZmLHAuSp3jU1SijGlVId7zmIXIaJ6pNVuNgpmNGRkHQdLsjdGUauEBi9U1BjR-esFvBHdfw.mp4?_nc_cat=104&_nc_sid=9ca052&_nc_ht=scontent-iad3-1.cdninstagram.com&_nc_ohc=ECX7BSThaXkQ7kNvwH-UVWe&efg=eyJ2ZW5jb2RlX3RhZyI6ImlnLXhwdmRzLmNsaXBzLmMyLUMyLmRhc2hfbG5faGVhYWNfdmJyM19hdWRpbyIsInZpZGVvX2lkIjpudWxsLCJvaWxfdXJsZ2VuX2FwcF9pZCI6OTM2NjE5NzQzMzkyNDU5LCJjbGllbnRfbmFtZSI6ImlnIiwieHB2X2Fzc2V0X2lkIjoxNzcxNTY1Njg3MTU0MjE1LCJhc3NldF9hZ2VfZGF5cyI6MTMsInZpX3VzZWNhc2VfaWQiOjEwODI3LCJkdXJhdGlvbl9zIjoxNCwiYml0cmF0ZSI6ODQxODcsInVybGdlbl9zb3VyY2UiOiJ3d3cifQ%3D%3D&ccb=17-1&_nc_gid=1dbJ6M6MmLLlo-Jn7XlUIw&_nc_zt=28&oh=00_AfvPFX3-VjMr5JtDwrX7wQkOILLeANNhb4zBuw9SU0DR3w&oe=6984DC3D", "createTime": 1769001195, "likeCount": 171650, "commentCount": 781, "userPk": "48143082417", "userName": "theavamariee", "userFullName": "Ava Marie", "avatarUri": "https://scontent-iad3-1.cdninstagram.com/v/t51.2885-19/572902973_18067009538602418_5617968281035790488_n.jpg?stp=dst-jpg_s150x150_tt6&efg=eyJ2ZW5jb2RlX3RhZyI6InByb2ZpbGVfcGljLmRqYW5nby4xMDgwLmMyIn0&_nc_ht=scontent-iad3-1.cdninstagram.com&_nc_cat=1&_nc_oc=Q6cZ2QHrB35R1hAV3-uIB5VTub-6RuiKV9psrvKni0oh6LvCvBnLGT24jt8xn1dfOPE5zM0&_nc_ohc=X48rTGGGJl8Q7kNvwFwYnWY&_nc_gid=1dbJ6M6MmLLlo-Jn7XlUIw&edm=APs17CUBAAAA&ccb=7-5&oh=00_AfvSE_cEd3Z5ja79s40JOWwAE3JIGmyySyCKLkoRBpTeJg&oe=6988A991&_nc_sid=10d13b", "text": "Excuse me, miss. What? Your shirt's backwards.", "segments": [ { "start": 0.3, "end": 1.16, "text": " Excuse me, miss." }, { "start": 1.32, "end": 1.62, "text": " What?" }, { "start": 2.04, "end": 2.96, "text": " Your shirt's backwards." } ], "errMsg": "", "timestamp": "2026-02-04T06:38:58.379Z" } ``` *** ### ⭐ Why This API Is Different 🚀 **Focused on transcripts, not noise** - 🧠 **AI-first design**\ Clean transcripts + timestamps, perfect for LLMs and agents. - 🎯 **Transcript over transformation**\ No summaries, no rewrites — just reliable raw text. - 💸 **Extremely cost-efficient**\ One of the lowest-cost Twitter transcript solutions available. - 📦 **Automation-safe**\ Stable fields, predictable structure, batch-friendly responses. - 🌍 **Built for real-world usage**\ Designed by a team experienced in large-scale social content extraction. *** ### 📝 Notes - Only **public Twitter videos** are supported - A valid `sessionid` improves stability and success rate - Transcript accuracy depends on audio clarity and language - Please ensure compliance with Twitter terms and local regulations - Free users can only try video transcription with a duration of no more than **5 minutes**, while paid users are not limited by the duration. *** ### 🆘 Support Questions, feedback, or feature requests? 📧 **Email:** support@apismith.online # Actor input Schema ## `videoUrl` (type: `string`): The URL of the twitter you want to get the data from. ## Actor input object example ```json { "videoUrl": "https://x.com/Dell_JPN/status/1975063471155970378" } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "videoUrl": "https://x.com/Dell_JPN/status/1975063471155970378" }; // Run the Actor and wait for it to finish const run = await client.actor("apple_yang/twitter-video-transcript-api").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 = { "videoUrl": "https://x.com/Dell_JPN/status/1975063471155970378" } # Run the Actor and wait for it to finish run = client.actor("apple_yang/twitter-video-transcript-api").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 '{ "videoUrl": "https://x.com/Dell_JPN/status/1975063471155970378" }' | apify call apple_yang/twitter-video-transcript-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apple_yang/twitter-video-transcript-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter Video Transcript API – AI Video to Text for X (Twitter)", "description": "Twitter Video Transcript API for converting video audio into accurate text using AI. Extract transcripts, spoken content, and metadata from X (Twitter) videos, tweets, and threads. Fast, reliable, and built for developers, AI agents, and automation workflows.", "version": "0.0", "x-build-id": "8yCdW9Yv3Dw1Xyo3v" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apple_yang~twitter-video-transcript-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apple_yang-twitter-video-transcript-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/apple_yang~twitter-video-transcript-api/runs": { "post": { "operationId": "runs-sync-apple_yang-twitter-video-transcript-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/apple_yang~twitter-video-transcript-api/run-sync": { "post": { "operationId": "run-sync-apple_yang-twitter-video-transcript-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "videoUrl" ], "properties": { "videoUrl": { "title": "The URL of the twitter", "type": "string", "description": "The URL of the twitter you want to get the data from." } } }, "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 } } } } } } } } } } ```