# Twitter / X Pro Scraper (`habit.zhou/twitter-pro-scraper`) Actor Four-mode Twitter / X scraper: keyword search, tweet detail by ID/URL, user profile + posts, trending topics. Returns text, author, likes, retweets, replies, views, media, language, publish time. No login. For sentiment, trends, KOL discovery, AI training data. - **URL**: https://apify.com/habit.zhou/twitter-pro-scraper.md - **Developed by:** [Seller Aim](https://apify.com/habit.zhou) (community) - **Categories:** Social media, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 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. 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 / X Pro Scraper Full-featured **Twitter / X** scraper. Four modes, one Actor, clean structured JSON. No login, no cookies, no broken-token surprises. Built for serious workloads — market sentiment research, KOL discovery, AI training pipelines harvesting English-language UGC, brand-watch dashboards, lead-generation lists, real-time event monitoring. ### What does this Actor do? Pick a mode, give it inputs, get a dataset: - **Keyword search** — search Twitter / X by keyword or full advanced query (`AI lang:en min_faves:100`). Five timeline types: Top, Latest, People, Media, Lists. - **Tweet detail by ID / URL** — paste a tweet ID or `twitter.com/user/status/` URL; get text, author, likes, retweets, replies, views, bookmarks, media URLs, language, publish time, and (optional) top replies. - **User profile + recent posts** — fetch a handle's profile (followers, bio, verified status, account age, location) and their recent tweets with pagination. - **Trending topics** — global trending list ordered by volume. Each tweet returns a flat, schema-validated JSON row that's downloadable as JSON, CSV, Excel, HTML, or XML — and queryable via the Apify REST API for pipeline integration. ### Why use Twitter / X Pro Scraper? - **No login, no breakage.** Other Twitter actors in the store rely on the user's logged-in cookie or `auth_token` that expires within days, or on credentials that get accounts banned. Customers end up with a stream of 401s and 1.5★ reviews. We use a maintained backend surface that stays stable. - **Four modes in one Actor.** Search, tweet, user, trending — pick a mode per run; no juggling separate Actors. - **Full-field output.** Text, author + screen name + uid, likes, retweets, replies, views, bookmarks, quotes, media URLs, language, publish time, conversation id, quoted tweet — all in one row. - **AI training-ready.** English UGC, clean JSON, deduplicable by `tweetId`. Drop straight into a vector DB, an LLM fine-tune set, or a sentiment classifier. - **Marketing dashboards.** Schedule keyword runs hourly and build a real-time pulse of any brand, product, ticker, or campaign on X. ### How to use 1. Open the Actor and click **Try for free**. 2. In the Input tab, pick a **Scrape mode** (search is the default). 3. Fill the inputs for your mode: - **search**: keywords + `searchType` (Top / Latest / People / Media / Lists) - **tweets**: tweet IDs or URLs in `tweetIds` - **user**: handles (without `@`) in `screenNames` - **trending**: nothing required 4. Set **Max items per input** (default 50). 5. Click **Save & Start**. Results stream into the dataset live. 6. Download or stream the dataset; schedule the run under the **Schedules** tab. ### Input | Field | Type | Used in mode | Description | |---|---|---|---| | `mode` | string | all | One of `search`, `tweets`, `user`, `trending`. | | `keywords` | array | search | Keywords or full Twitter advanced-search queries. | | `searchType` | enum | search | `Top` / `Latest` / `People` / `Media` / `Lists`. | | `tweetIds` | array | tweets | Numeric tweet IDs or full URLs. | | `screenNames` | array | user | Twitter / X handles (without `@`). | | `maxItemsPerInput` | integer (1–1000) | all | Cap per keyword / tweet / user. Default 50. | | `fetchComments` | boolean | tweets | Fetch up to 20 top replies per tweet. Extra cost. | JSON example — keyword search: ```json { "mode": "search", "keywords": ["claude code", "AI lang:en min_faves:100"], "searchType": "Latest", "maxItemsPerInput": 100 } ```` ### Output ```json { "tweetId": "2056362875195686927", "text": "the engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work...", "author": "Anatoli Kopadze", "screenName": "AnatoliKopadze", "userId": "1234567890", "likes": 23714, "retweets": 4098, "replies": 189, "quotes": 56, "views": 6018031, "bookmarks": 59314, "isVideo": false, "media": ["https://pbs.twimg.com/.../photo.jpg"], "lang": "en", "publishedAt": "2026-05-18T13:14:49.000Z", "tweetUrl": "https://twitter.com/AnatoliKopadze/status/2056362875195686927", "conversationId": "2056362875195686927", "quotedTweetId": null, "keyword": "claude code", "searchType": "Latest", "scrapedAt": "2026-05-22T13:30:01.000Z" } ``` #### Output fields | Field | Description | |---|---| | `tweetId` | Numeric tweet ID (canonical). | | `text` | Tweet body (full text, not truncated). | | `author` | Display name of the author. | | `screenName` | Author handle (no `@`). | | `userId` | Numeric user ID — pair with `mode: "user"` to drill in. | | `likes` | Favorite / like count. | | `retweets` | Retweet count. | | `replies` | Reply count. | | `quotes` | Quote-tweet count. | | `views` | View count. | | `bookmarks` | Bookmark count. | | `isVideo` | True if the tweet includes a video. | | `media` | All media URLs (videos first, then photos). | | `lang` | Twitter-detected language code. | | `publishedAt` | ISO 8601 publish time. | | `tweetUrl` | Public deep link. | | `conversationId` | ID of the root tweet for the thread. | | `quotedTweetId` | ID of the quoted tweet, if this is a quote-tweet. | | `replies` (when `fetchComments`) | Top 20 reply tweets. | | `userProfile` | Author profile object (user mode only). | | `scrapedAt` | ISO 8601 timestamp of scrape. | ### Pricing **$1.99 per 1,000 results.** Each tweet returned counts as one result. `tweets` mode with `fetchComments=true` returns richer rows but is billed at the same rate. #### Free vs. paid Apify plans Apify free-plan users get **2 sample runs capped at 10 results each** so you can verify the data shape and quality before committing. Further runs from free accounts are blocked with an upgrade prompt — this Actor relies on a paid backend, so we can't subsidise unlimited free use. Any Apify paid plan ($49/month and up — see [Apify pricing](https://apify.com/pricing)) unlocks unlimited runs at the rate above. #### Cost estimates | Goal | Items / run | Mode | Est. cost / run | |---|---|---|---| | Quick scan of one keyword | 50 | search | ~$0.20 | | Brand round-up | 500 | search | ~$2.00 | | KOL deep dive | 200 tweets | user | ~$0.80 | | Daily ticker monitoring | 1,000 | search | ~$4.00 / day | Apify also charges a small compute fee (typically $0.01-0.05 per minute of run time). ### Tips - **Use Twitter advanced search syntax.** `AI lang:en min_faves:100 since:2026-01-01` filters at the source — fewer wasted billed rows. - **Schedule, don't poll.** For breaking news / event monitoring, schedule every 5-15 minutes during peak hours. - **Deduplicate by `tweetId`.** Sequential runs overlap; merge and dedupe on `tweetId`. - **Pair user + tweets modes.** Use `mode: "user"` to find KOLs, then drill into top tweets with `mode: "tweets"` + `fetchComments`. - **`searchType: "Top"` vs `Latest`.** Top surfaces high-engagement tweets; Latest is firehose. Pick based on whether you want signal or recency. ### FAQ **Q: Why is this Actor different from the other Twitter scrapers on the Store?** A: Most existing actors depend on customer-provided `auth_token` / cookies that expire fast or get accounts banned. We don't ask for credentials. We've engineered around stable backend surfaces so the Actor stays usable across token rotations. **Q: Will this break when Twitter / X changes their API?** A: Possibly. Our team maintains the backend; we patch usually within 24-72 hours of a backend change. Bug reports via the Issues tab. **Q: Is scraping Twitter / X legal?** A: We pull only publicly-accessible content — what any visitor can see without logging in. Your usage is your responsibility; comply with your jurisdiction's law and X's Terms of Service. Do not use the data to identify or target individuals. **Q: Can I get my data via API?** A: Yes. Every Apify run exposes a stable [REST API](https://docs.apify.com/api/v2) for inputs, datasets, and run status. Plug into n8n, Make, Zapier, or your own pipeline. **Q: Is there a free tier?** A: The Apify platform gives every new account $5 in free credit — enough for ~1,000 results to evaluate the Actor before committing. **Q: How fast are runs?** A: Search: ~3 seconds per page (~20 tweets). User: ~2 seconds per page. Tweet detail: ~1 second per tweet. Trending: ~1 second total. **Q: I need a richer integration or higher-volume contract.** A: Reach out via Apify chat. Custom endpoints and SLAs available on request. # Actor input Schema ## `mode` (type: `string`): What to pull from Twitter / X. ## `keywords` (type: `array`): Keywords or queries. Supports Twitter advanced search syntax (e.g. 'AI lang:en min\_faves:100'). ## `searchType` (type: `string`): Which timeline tab to scrape from. ## `tweetIds` (type: `array`): Tweet IDs or full URLs (twitter.com/user/status/). ## `screenNames` (type: `array`): Twitter / X handles without '@'. ## `maxItemsPerInput` (type: `integer`): Cap per keyword / tweet / user. Each item returned is one billed result. ## `fetchComments` (type: `boolean`): When on, fetches up to 20 top replies per tweet (tweets mode only). Extra cost per tweet. ## Actor input object example ```json { "mode": "search", "keywords": [ "AI" ], "searchType": "Latest", "tweetIds": [], "screenNames": [], "maxItemsPerInput": 50, "fetchComments": false } ``` # Actor output Schema ## `dataset` (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 = { "keywords": [ "AI" ] }; // Run the Actor and wait for it to finish const run = await client.actor("habit.zhou/twitter-pro-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 = { "keywords": ["AI"] } # Run the Actor and wait for it to finish run = client.actor("habit.zhou/twitter-pro-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 '{ "keywords": [ "AI" ] }' | apify call habit.zhou/twitter-pro-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=habit.zhou/twitter-pro-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter / X Pro Scraper", "description": "Four-mode Twitter / X scraper: keyword search, tweet detail by ID/URL, user profile + posts, trending topics. Returns text, author, likes, retweets, replies, views, media, language, publish time. No login. For sentiment, trends, KOL discovery, AI training data.", "version": "0.1", "x-build-id": "xpbEBdxaYHOu4VkeL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/habit.zhou~twitter-pro-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-habit.zhou-twitter-pro-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/habit.zhou~twitter-pro-scraper/runs": { "post": { "operationId": "runs-sync-habit.zhou-twitter-pro-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/habit.zhou~twitter-pro-scraper/run-sync": { "post": { "operationId": "run-sync-habit.zhou-twitter-pro-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode" ], "properties": { "mode": { "title": "Scrape mode", "enum": [ "search", "tweets", "user", "trending" ], "type": "string", "description": "What to pull from Twitter / X.", "default": "search" }, "keywords": { "title": "Search keywords (search mode)", "uniqueItems": true, "type": "array", "description": "Keywords or queries. Supports Twitter advanced search syntax (e.g. 'AI lang:en min_faves:100').", "items": { "type": "string" } }, "searchType": { "title": "Search type (search mode)", "enum": [ "Top", "Latest", "People", "Media", "Lists" ], "type": "string", "description": "Which timeline tab to scrape from.", "default": "Latest" }, "tweetIds": { "title": "Tweet IDs or URLs (tweets mode)", "type": "array", "description": "Tweet IDs or full URLs (twitter.com/user/status/).", "default": [], "items": { "type": "string" } }, "screenNames": { "title": "User handles (user mode)", "type": "array", "description": "Twitter / X handles without '@'.", "default": [], "items": { "type": "string" } }, "maxItemsPerInput": { "title": "Max items per input", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Cap per keyword / tweet / user. Each item returned is one billed result.", "default": 50 }, "fetchComments": { "title": "Also fetch top replies per tweet", "type": "boolean", "description": "When on, fetches up to 20 top replies per tweet (tweets mode only). Extra cost per tweet.", "default": false } } }, "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 } } } } } } } } } } ```