# Twitter / X Scraper Unlimited – Tweets, Profiles & Hashtags (`dev-sinior/twitter-scraper-unlimited`) Actor Extract tweets, profiles, followers and hashtags from X.com (Twitter) with no volume limits. Search by keyword, date, language or user. Pay-per-event pricing. Exports to JSON & CSV. - **URL**: https://apify.com/dev-sinior/twitter-scraper-unlimited.md - **Developed by:** [DEV-SINIOR](https://apify.com/dev-sinior) (community) - **Categories:** Social media, News, Videos - **Stats:** 4 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 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 undefined # Actor input Schema ## `mode` (type: `string`): What to scrape: search results, user profile, user tweets, or hashtag. ## `queries` (type: `array`): Search: keywords. Profile/Tweets: usernames (without @). Hashtag: tags (without #). ## `maxItems` (type: `integer`): Maximum tweets or profiles to collect per query. ## `language` (type: `string`): Filter by language code (e.g. 'en', 'fr', 'es'). Leave empty for all. ## `fromDate` (type: `string`): Only tweets after this date. Format: YYYY-MM-DD ## `toDate` (type: `string`): Only tweets before this date. Format: YYYY-MM-DD ## `includeReplies` (type: `boolean`): Include reply tweets in results. ## `includeRetweets` (type: `boolean`): Include retweets in results. ## `proxyCountry` (type: `string`): Country code for residential proxy (recommended: US). ## Actor input object example ```json { "mode": "search", "queries": [ "artificial intelligence", "web scraping 2026" ], "maxItems": 100, "language": "en", "fromDate": "2024-01-01", "toDate": "2024-12-31", "includeReplies": false, "includeRetweets": true, "proxyCountry": "US" } ```` # Actor output Schema ## `type` (type: `string`): tweet or profile ## `id` (type: `string`): Tweet ID ## `text` (type: `string`): Full tweet content ## `createdAt` (type: `string`): Tweet creation timestamp (ISO) ## `lang` (type: `string`): Tweet language code ## `likeCount` (type: `string`): Number of likes ## `retweetCount` (type: `string`): Number of retweets ## `replyCount` (type: `string`): Number of replies ## `quoteCount` (type: `string`): Number of quote tweets ## `bookmarkCount` (type: `string`): Number of bookmarks ## `viewCount` (type: `string`): Number of views/impressions ## `isRetweet` (type: `string`): Whether tweet is a retweet ## `isQuote` (type: `string`): Whether tweet is a quote tweet ## `isReply` (type: `string`): Whether tweet is a reply ## `hasMedia` (type: `string`): Whether tweet contains media ## `hashtags` (type: `string`): Hashtags in the tweet ## `mentions` (type: `string`): Mentioned usernames ## `url` (type: `string`): Direct link on x.com ## `twitterUrl` (type: `string`): Direct link on twitter.com ## `keyword` (type: `string`): Search query that returned this ## `authorUsername` (type: `string`): Author @username ## `authorName` (type: `string`): Author display name ## `authorFollowers` (type: `string`): Author follower count ## `authorVerified` (type: `string`): Blue checkmark ## `authorImageUrl` (type: `string`): Author profile image URL # 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("dev-sinior/twitter-scraper-unlimited").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("dev-sinior/twitter-scraper-unlimited").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 dev-sinior/twitter-scraper-unlimited --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dev-sinior/twitter-scraper-unlimited", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter / X Scraper Unlimited – Tweets, Profiles & Hashtags", "description": "Extract tweets, profiles, followers and hashtags from X.com (Twitter) with no volume limits. Search by keyword, date, language or user. Pay-per-event pricing. Exports to JSON & CSV.", "version": "1.0", "x-build-id": "aZ6MUSPs5RbRZTlbP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dev-sinior~twitter-scraper-unlimited/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dev-sinior-twitter-scraper-unlimited", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dev-sinior~twitter-scraper-unlimited/runs": { "post": { "operationId": "runs-sync-dev-sinior-twitter-scraper-unlimited", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dev-sinior~twitter-scraper-unlimited/run-sync": { "post": { "operationId": "run-sync-dev-sinior-twitter-scraper-unlimited", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "mode": { "title": "Scraping Mode", "enum": [ "search", "hashtag", "profile", "tweets" ], "type": "string", "description": "What to scrape: search results, user profile, user tweets, or hashtag.", "default": "search" }, "queries": { "title": "Keywords / Usernames / Hashtags", "type": "array", "description": "Search: keywords. Profile/Tweets: usernames (without @). Hashtag: tags (without #).", "items": { "type": "string" } }, "maxItems": { "title": "Max Items per Query", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum tweets or profiles to collect per query.", "default": 100 }, "language": { "title": "Language Filter", "type": "string", "description": "Filter by language code (e.g. 'en', 'fr', 'es'). Leave empty for all." }, "fromDate": { "title": "From Date", "type": "string", "description": "Only tweets after this date. Format: YYYY-MM-DD" }, "toDate": { "title": "To Date", "type": "string", "description": "Only tweets before this date. Format: YYYY-MM-DD" }, "includeReplies": { "title": "Include Replies", "type": "boolean", "description": "Include reply tweets in results.", "default": false }, "includeRetweets": { "title": "Include Retweets", "type": "boolean", "description": "Include retweets in results.", "default": true }, "proxyCountry": { "title": "Proxy Country", "type": "string", "description": "Country code for residential proxy (recommended: US).", "default": "US" } } }, "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 } } } } } } } } } } ```