# Twitter/X Search Scraper ยท No Cookies (`data-slayer/twitter-search`) Actor Search Twitter/X and extract tweets matching any keyword, hashtag, or mention without login. Get full tweet text, likes, retweets, views, bookmarks, user profiles, media URLs, and conversation threads. No cookies, no API key. JSON/CSV/Excel export. - **URL**: https://apify.com/data-slayer/twitter-search.md - **Developed by:** [Data Slayer](https://apify.com/data-slayer) (community) - **Categories:** Social media, Automation, Lead generation - **Stats:** 225 total users, 58 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## 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 Search Scraper ยท No Cookies Extract real-time Twitter search results without authentication or cookies. This scraper delivers comprehensive tweet data, engagement metrics, and user profiles for sales intelligence, competitive analysis, and lead generation โ€” all without requiring a Twitter account. ### ๐Ÿ“บ Video Tutorial: How it Works [https://www.youtube.com/watch?v=TPMUFKPdXiE](https://www.youtube.com/watch?v=TPMUFKPdXiE) --- ### Inputs | Field | Type | Description | | ----- | ------ | ------------------------------------------------------------------------------------------------------------------------ | | query | String | Twitter search query (e.g., "Mr Beast", "#AI", "@username", or advanced operators like "from:user" or "filter:verified") | ### Outputs **Formats**: JSON, CSV, Excel **Key Fields**: - `tweet_id` - Unique tweet identifier - `screen_name` - Author's Twitter handle - `text` - Full tweet content - `created_at` - Publication timestamp - `favorites` - Like count - `retweets` - Retweet count - `bookmarks` - Bookmark count - `views` - View count - `replies` - Reply count - `quotes` - Quote tweet count - `conversation_id` - Thread identifier - `entities.hashtags` - Extracted hashtags with positions - `entities.user_mentions` - Mentioned users with IDs - `entities.media` - Attached photos/videos with URLs - `user_info.followers_count` - Author's follower count - `user_info.verified` - Verification status - `user_info.description` - User bio - `user_info.avatar` - Profile image URL - `lang` - Tweet language code - `source` - Publishing platform ### Sample Output ```json { "type": "tweet", "tweet_id": "1734567890123456789", "screen_name": "tech_innovator", "text": "Excited to announce our new AI product launch! Join us tomorrow for the live demo. #TechLaunch #Innovation", "created_at": "Mon Dec 16 14:23:15 +0000 2025", "favorites": 2847, "retweets": 456, "bookmarks": 189, "views": "87432", "replies": 34, "quotes": 12, "conversation_id": "1734567890123456789", "lang": "en", "entities": { "hashtags": [ {"text": "TechLaunch", "indices": [82, 93]}, {"text": "Innovation", "indices": [94, 105]} ], "user_mentions": [], "media": [] }, "user_info": { "screen_name": "tech_innovator", "name": "Tech Innovator", "followers_count": 45678, "verified": true, "description": "Building the future of AI | Speaker | Investor", "avatar": "https://pbs.twimg.com/profile_images/example.jpg" } } ```` *** ### How to Use **Step 1**: Enter your search query in the `query` field (supports keywords, hashtags, mentions, and Twitter's advanced search operators). **Step 2**: Configure optional parameters like maximum results or date filters based on your data collection needs. **Step 3**: Run the scraper and download results in your preferred format (JSON for technical integration, CSV/Excel for business analysis). ### Key Features ๐Ÿ”’ **Cookieless / No Login Required** - Access public Twitter search data without authentication, eliminating account suspension risks and credential management overhead. ๐Ÿ“ˆ **Scalable Architecture** - Process thousands of search results efficiently with built-in rate limiting and proxy rotation for enterprise-grade data collection. โœ… **Rich Tweet & Profile Data** - Capture complete tweet metadata including engagement metrics (favorites, retweets, bookmarks, views), user profiles (followers, verification status, bio), hashtags, mentions, media URLs, and conversation threads. โšก **Fast & Reliable** - Optimized extraction engine delivers results in minutes with automatic retry logic and error handling for uninterrupted data collection. ๐Ÿ“Š **Export-Ready Formats** - Download data instantly in JSON, CSV, or Excel formats compatible with CRM systems, analytics platforms, and business intelligence tools. ### Use Cases **Sales Intelligence Teams**: Monitor brand mentions, competitor activity, and industry conversations to identify warm leads and track customer sentiment in real-time for targeted outreach campaigns. **Market Research Analysts**: Aggregate trending topics, hashtag performance, and engagement patterns to build comprehensive competitive intelligence databases and identify emerging market opportunities. **Growth Marketers**: Track campaign hashtags, influencer mentions, and viral content metrics to optimize social media strategies and measure brand awareness across target demographics. ### ๐Ÿงฉ Other Twitter/X Actors by Data Slayer | Actor | What it does | Link | | --------------------------------- | ------------------------------------------ | ------------------------------------------------------------------ | | Twitter Tweets Scraper | Extract tweets from any Twitter/X account | [Try it](https://apify.com/data-slayer/twitter-user-tweets) | | Twitter Comments Scraper | Extract replies from any tweet | [Try it](https://apify.com/data-slayer/twitter-comments) | | Twitter Followers Scraper | Extract follower lists from any account | [Try it](https://apify.com/data-slayer/twitter-followers) | | Twitter Following Scraper | See who any account follows | [Try it](https://apify.com/data-slayer/twitter-followings) | | Twitter Profile Scraper | Get detailed profile data by username | [Try it](https://apify.com/data-slayer/twitter-user) | | Twitter List Members Scraper | Extract members from any Twitter list | [Try it](https://apify.com/data-slayer/twitter-list-members) | | Twitter Community Members Scraper | Extract members from any Twitter community | [Try it](https://apify.com/data-slayer/twitter-community-members) | | Twitter Trends Scraper | Get trending topics by location | [Try it](https://apify.com/data-slayer/twitter-trends-by-location) | **Need verified emails?** Our [LinkedIn Post Engagers Email Finder](https://apify.com/data-slayer/linkedin-post-to-verified-leads) and [LinkedIn Audience Email Finder](https://apify.com/data-slayer/linkedin-influencer-audience-to-verified-leads) extract verified work emails from LinkedIn engagement data. ### ๐Ÿ’ฌ Feedback and Support We actively maintain this actor and ship improvements based on user feedback. If you run into any issues or have ideas for new features: - Create an issue on the Actor's **Issues tab** in Apify Console - Rate the actor if it helped you โ€” it helps others find it too We typically respond within 24 hours. *** *** # Actor input Schema ## `query` (type: `string`): Search query ## `section` (type: `string`): Section: top, latest, people, photos, videos ## `maxPages` (type: `integer`): Maximum number of pages to fetch (pagination handled automatically) ## Actor input object example ```json { "query": "new york", "section": "top", "maxPages": 1 } ``` # 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("data-slayer/twitter-search").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 = {} # Run the Actor and wait for it to finish run = client.actor("data-slayer/twitter-search").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 '{}' | apify call data-slayer/twitter-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data-slayer/twitter-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter/X Search Scraper ยท No Cookies", "description": "Search Twitter/X and extract tweets matching any keyword, hashtag, or mention without login. Get full tweet text, likes, retweets, views, bookmarks, user profiles, media URLs, and conversation threads. No cookies, no API key. JSON/CSV/Excel export.", "version": "1.0", "x-build-id": "3M4mVVTlzksJ2kmPL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data-slayer~twitter-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data-slayer-twitter-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data-slayer~twitter-search/runs": { "post": { "operationId": "runs-sync-data-slayer-twitter-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data-slayer~twitter-search/run-sync": { "post": { "operationId": "run-sync-data-slayer-twitter-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search query", "type": "string", "description": "Search query", "default": "new york" }, "section": { "title": "Section: top, latest, people, photos, videos", "type": "string", "description": "Section: top, latest, people, photos, videos", "default": "top" }, "maxPages": { "title": "Maximum Pages", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of pages to fetch (pagination handled automatically)", "default": 1 } } }, "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 } } } } } } } } } } ```