# X/Twitter Search Scraper (`scrapesmith/x-twitter-search-scraper`) Actor Search X (Twitter) by keyword, hashtag, phrase or username. Sort by Latest, Top or Media. Filter by language. Get full tweet text, engagement metrics, author details and media URLs. Handles thousands of results per query automatically. - **URL**: https://apify.com/scrapesmith/x-twitter-search-scraper.md - **Developed by:** [Scrape Smith](https://apify.com/scrapesmith) (community) - **Categories:** Social media, Developer tools, Automation - **Stats:** 5 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.15 / 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 ## X (Twitter) Search Scraper Search **X (Twitter)** for tweets by keyword, hashtag, phrase, or username — in real time, at scale, with no login required. Whether you're tracking a brand mention, watching a trending topic, or researching a competitor's audience, this scraper pulls matching tweets straight into a clean, structured dataset ready for analysis. --- ### What it does Give it one or more search terms — a keyword, a `#hashtag`, a phrase, or an advanced query like `from:username` — and it returns matching tweets with full text, engagement numbers, media, and author details. No X account, login, or cookies needed to run it. ### Key features - **Real-time search** — results reflect what's on X right now, not a cached snapshot. - **Sort by Latest, Top, or Media** — choose the most recent tweets, the most engaging ones, or tweets that include photos/video. - **Language filter** — restrict results to a single language (e.g. English, Spanish, Japanese) using a simple 2-letter code. - **Deep pagination** — collect anywhere from a handful of tweets up to tens of thousands per search. - **Automatic large-result handling** — for very popular or broad queries, the scraper automatically pulls in additional historical results beyond what a single search normally surfaces, so you don't have to split queries yourself. - **Multiple search terms per run** — queue up several searches at once and get all the results in a single dataset. ### Input parameters | Parameter | Type | Description | |---|---|---| | `searchTerms` | array of strings | One or more search queries, e.g. `"apple vision pro"`, `"#AI"`, `"from:elonmusk"`. Supports X's advanced search operators. | | `sort` | string | Result order: `Latest`, `Top`, or `Media`. Default: `Latest`. | | `maxTweets` | integer | Maximum tweets to collect **per search term**. Default: `100`. | | `tweetLanguage` | string | Optional 2-letter language code (e.g. `en`, `es`, `ja`) to filter results. | | `maxItems` | integer | Optional overall cap on total tweets across all search terms combined. | #### Supported search operators Use these directly inside any search term: - `from:username` — tweets from a specific account - `since:2026-01-01 until:2026-06-01` — a date range - `#hashtag` — hashtag search - `"exact phrase"` — exact match - `-filter:replies` — exclude replies ### Output fields Each result is a tweet object with: | Field | Description | |---|---| | `id` / `url` | Tweet ID and direct link | | `text` | Full tweet text | | `createdAt` | Publish timestamp | | `likeCount`, `retweetCount`, `replyCount`, `quoteCount` | Engagement metrics | | `viewCount` | View count | | `isRetweet` / `isReply` / `isQuote` | Tweet type flags | | `hashtags`, `mentions`, `urls` | Extracted entities | | `media` | Image and video URLs attached to the tweet | | `quotedTweet` | Full nested tweet object, when the tweet quotes another | | `author` | Username, display name, follower count, verification status, bio, profile picture, and more | ### Example input ```json { "searchTerms": ["apple vision pro", "#AI"], "sort": "Latest", "maxTweets": 500, "tweetLanguage": "en" } ```` ### Example output ```json { "type": "tweet", "id": "1987654321098765432", "url": "https://x.com/username/status/1987654321098765432", "text": "Just tried the new update and it's incredible...", "createdAt": "2026-07-01T12:00:00.000Z", "likeCount": 245, "retweetCount": 38, "replyCount": 12, "viewCount": 18204, "hashtags": ["AI"], "author": { "userName": "username", "name": "Display Name", "followers": 12500, "verified": true } } ``` ### Cost and pricing This actor uses the **Pay Per Result** model — you're only charged for each tweet returned, with no separate compute cost to worry about. There's a free tier included on every Apify plan, so you can try it before committing to a larger run. ### Use cases - **Brand monitoring** — track every mention of your brand, product, or campaign hashtag as it happens. - **Trend analysis** — pull large volumes of tweets on a topic to measure sentiment, volume, and momentum over time. - **Competitor research** — see what people are saying about competitors, or pull a competitor's own tweets with `from:username`. - **Market and audience research** — analyze engagement patterns and audience reactions around any keyword or hashtag. - **Content discovery** — find high-performing posts on a topic by sorting for `Top` results. ### FAQ **Do I need a Twitter/X account?** No — no login, cookies, or account setup required. **Can I search by hashtag or user?** Yes — use `#hashtag` or `from:username` as a search term. **Which languages are supported?** Any tweet language; use the language filter to narrow results to a single 2-letter ISO code (e.g. `en`, `es`, `ja`). **How many results can I get per search?** Anywhere from a few tweets up to tens of thousands, depending on how popular the query is — set `maxTweets` to control the cap. **What formats can I export?** JSON, CSV, Excel, HTML table, or pull results directly via the Apify API. # Actor input Schema ## `searchTerms` (type: `array`): Search queries to run, e.g. 'apple vision pro', '#AI', 'from:elonmusk'. Twitter's advanced search operators are supported. ## `sort` (type: `string`): Result ordering for each search. ## `maxTweets` (type: `integer`): Maximum number of tweets to collect for each search term. ## `tweetLanguage` (type: `string`): Only return tweets in this language. 2-letter ISO code, e.g. 'en', 'es', 'ja'. ## `maxItems` (type: `integer`): Overall cap on tweets collected across all search terms. Leave empty for as many as possible. ## Actor input object example ```json { "searchTerms": [ "apple vision pro" ], "sort": "Latest", "maxTweets": 100, "tweetLanguage": "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 = { "searchTerms": [ "apple vision pro" ], "tweetLanguage": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesmith/x-twitter-search-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 = { "searchTerms": ["apple vision pro"], "tweetLanguage": "en", } # Run the Actor and wait for it to finish run = client.actor("scrapesmith/x-twitter-search-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 '{ "searchTerms": [ "apple vision pro" ], "tweetLanguage": "en" }' | apify call scrapesmith/x-twitter-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesmith/x-twitter-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X/Twitter Search Scraper", "description": "Search X (Twitter) by keyword, hashtag, phrase or username. Sort by Latest, Top or Media. Filter by language. Get full tweet text, engagement metrics, author details and media URLs. Handles thousands of results per query automatically.", "version": "0.0", "x-build-id": "zxKccYphNTcHEyoC4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesmith~x-twitter-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesmith-x-twitter-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapesmith~x-twitter-search-scraper/runs": { "post": { "operationId": "runs-sync-scrapesmith-x-twitter-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapesmith~x-twitter-search-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesmith-x-twitter-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchTerms" ], "properties": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Search queries to run, e.g. 'apple vision pro', '#AI', 'from:elonmusk'. Twitter's advanced search operators are supported.", "items": { "type": "string" } }, "sort": { "title": "Sort by", "enum": [ "Top", "Latest", "Media" ], "type": "string", "description": "Result ordering for each search.", "default": "Latest" }, "maxTweets": { "title": "Max tweets per search", "minimum": 1, "type": "integer", "description": "Maximum number of tweets to collect for each search term.", "default": 100 }, "tweetLanguage": { "title": "Tweet language", "type": "string", "description": "Only return tweets in this language. 2-letter ISO code, e.g. 'en', 'es', 'ja'." }, "maxItems": { "title": "Max total items", "minimum": 1, "type": "integer", "description": "Overall cap on tweets collected across all search terms. Leave empty for as many as possible." } } }, "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 } } } } } } } } } } ```