# Twitter User By Username (`monumental_world/twitter-user`) Actor Get Twitter user by username. - **URL**: https://apify.com/monumental\_world/twitter-user.md - **Developed by:** [Raised Pro](https://apify.com/monumental_world) (community) - **Categories:** Social media - **Stats:** 7 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. 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 (X.com) User Export (cookieless / no login needed) to Excel ### Need to download Twitter (X.com) data to Excel? This tool helps you extract user profiles instantly. Whether you're a sales intelligence professional, agency owner, or business developer, this tool makes it easy to retrieve detailed Twitter user information and export it directly to Excel or CSV. No technical skills required, and best of allโ€”no login needed! Perfect for enriching your lead databases, researching prospects, and personalizing your outreach strategies with real social media insights. ### Step-by-Step Guide **Step 1: Enter the Twitter Username** Simply type in the Twitter username you want to look up (for example: ""elonmusk""). No need to include the @ symbol or full URLโ€”just the username itself. **Step 2: Click ""Start""** Hit the start button and let the tool do its work. No Twitter account or login credentials required. The tool works completely cookieless, so you can extract data without any authentication hassles. **Step 3: Download Your Data** Once the extraction is complete, download your results as an Excel file (.xlsx), CSV, or XML format. Open it in Excel, Google Sheets, or any spreadsheet program you prefer. ### What columns will I get? Your download will include the following columns: - **User ID** - Unique identifier for the Twitter account - **Username** - The Twitter handle - **Email Address** - Associated email (when available) - **Account Creation Date** - When the account was created - **Last Login Date** - Most recent login timestamp - **Total Posts Count** - Number of tweets posted - **Follower Count** - How many followers the user has - **Following Count** - How many accounts the user follows - **Profile Verified** - Whether the account has verification status - **Account Status** - Current status (active, suspended, etc.) - **Login Attempts Last 24h** - Recent login activity - **Last IP Address** - Most recent IP used ### How to use this data Here are three simple ways sales intelligence professionals can put this data to work: **1. Enrich Your Lead Database** Import the follower counts, verification status, and account creation dates directly into your CRM. This helps you prioritize high-value prospects and understand their social media presence before reaching out. **2. Personalize Your Outreach** Use the total posts count and following/follower ratio to craft personalized messages. For example, if someone has a large following, acknowledge their influence. If they're newer to Twitter, tailor your approach accordingly. **3. Build Targeted Prospect Lists** Filter the Excel file by follower count or verification status to identify influencers, decision-makers, or active users in your target market. Sort and segment your leads based on real social media metrics. ### Input Settings **Username** Enter the Twitter username you want to look up. This is the handle that appears after the @ symbol on Twitter. For example, if you want to look up Elon Musk's profile, simply enter: **elonmusk** Don't include the @ symbol, just the username itself. The tool will handle the rest and retrieve all available profile information for that user. ### Frequently Asked Questions **Q: Do I need a Twitter (X.com) account?** No! This tool works completely cookieless and doesn't require any login credentials. You can extract user data without having a Twitter account or being logged in. **Q: Can I open this in Google Sheets?** Yes! Simply download the CSV format and upload it to Google Sheets. You can also open Excel files directly in Google Sheets by uploading the .xlsx file to your Google Drive. **Q: How accurate is the data?** The tool retrieves real-time data directly from Twitter profiles, so you're getting the most current information available at the time of extraction. **Q: Is there a limit to how many profiles I can export?** This depends on your usage plan, but the tool is designed to handle both single profile lookups and bulk extractions efficiently. --- *Related searches: username scraper, get user by username, profile scraper tool, export user profiles, social media username lookup, lead generation scraper, profile data extraction*" # Actor input Schema ## `username` (type: `string`): Username ## Actor input object example ```json { "username": "elonmusk" } ```` # 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 = { "username": "elonmusk" }; // Run the Actor and wait for it to finish const run = await client.actor("monumental_world/twitter-user").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "username": "elonmusk" } # Run the Actor and wait for it to finish run = client.actor("monumental_world/twitter-user").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "username": "elonmusk" }' | apify call monumental_world/twitter-user --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=monumental_world/twitter-user", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter User By Username", "description": "Get Twitter user by username.", "version": "1.0", "x-build-id": "D2ueFpQrJ0wOGGW3X" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/monumental_world~twitter-user/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-monumental_world-twitter-user", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/monumental_world~twitter-user/runs": { "post": { "operationId": "runs-sync-monumental_world-twitter-user", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/monumental_world~twitter-user/run-sync": { "post": { "operationId": "run-sync-monumental_world-twitter-user", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "Username", "type": "string", "description": "Username", "default": "elonmusk" } } }, "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 } } } } } } } } } } ```