# Twitter (X) Search Scraper - Tweets by Keyword & Query (`dami_studio/twitter-search-scraper`) Actor Scrape X (Twitter) search by keyword or advanced query (from:, min\_faves:, filter:media, date ranges). Returns full text, engagement, author & media. Export JSON/CSV/Excel or Notion. $0.30/1k tweets - cheaper than the big providers, and failed runs are free. - **URL**: https://apify.com/dami\_studio/twitter-search-scraper.md - **Developed by:** [Dami's Studio](https://apify.com/dami_studio) (community) - **Categories:** Social media, Lead generation - **Stats:** 6 total users, 5 monthly users, 93.5% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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) Search Scraper - Tweets by Keyword ⚡ Scrape X (Twitter) SEARCH results by keyword/query (supports from:, min_faves:, filter:media, date operators). Uses your logged-in account cookies (rotated across a pool, like the paid services) — X search has no keyless path. Returns full text, engagement, author, media. Export JSON/CSV/Excel or deliver to Notion. Pay per tweet. ### ⚠️ Requires a logged-in account cookie for real data X gates search and lists behind a login — every provider (including the big paid ones) scrapes these with **pools of logged-in accounts**. This actor does the same with **your** account cookies, rotating across them and backing off on rate-limits. > **Run it with no cookies first?** Without `sessionCookies` the actor runs in a free **demo mode** and returns one clearly-labeled `_sample` tweet so you can preview the output shape. Add cookies for real search results. **How to get the cookie (1 minute):** 1. Log in to **x.com** in your browser (use a throwaway account you don't mind risking). 2. Press **F12** → **Application** tab → **Cookies** → `https://x.com`. 3. Copy the values of **`auth_token`** and **`ct0`**. 4. Paste into `sessionCookies` as: `auth_token=XXXX; ct0=YYYY` — add several accounts (one per line) for more throughput; the actor rotates them. > Throwaway accounts get rate-limited/flagged over time — add a few and top them up occasionally (same as the paid services do). ### Pricing **$0.30 per 1,000 tweets** (pay-per-result). Failed/empty runs cost nothing. # Actor input Schema ## `searchTerms` (type: `array`): X search queries (advanced operators supported). ## `sort` (type: `string`): Newest or most relevant. ## `maxItems` (type: `integer`): Charged per tweet. ## `since` (type: `string`): YYYY-MM-DD ## `until` (type: `string`): YYYY-MM-DD ## `onlyVerifiedUsers` (type: `boolean`): Keep only verified authors. ## `sessionCookies` (type: `array`): X requires a logged-in session for search/lists — this is how every paid service does it. WITHOUT cookies the actor returns one clearly-labeled SAMPLE tweet (free demo mode) so you can preview the output shape. For real results add one or more throwaway-account cookies; the actor rotates them on rate-limit. From a logged-in x.com: F12 → Application → Cookies → copy auth_token and ct0. Paste each account as 'auth_token=XXXX; ct0=YYYY' (one per line). ## `proxyConfiguration` (type: `object`): Residential proxy strongly recommended (paid services use residential to protect the accounts). ## `notionConnector` (type: `string`): Optional Notion delivery. ## `notionParentId` (type: `string`): Optional Notion data-source id. ## Actor input object example ```json { "searchTerms": [ "\"web scraping\" min_faves:50", "from:nasa" ], "sort": "Latest", "maxItems": 100, "since": "2024-01-01", "until": "2024-12-31", "onlyVerifiedUsers": false, "sessionCookies": [ "auth_token=abcd1234...; ct0=ef567890..." ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # Actor output Schema ## `results` (type: `string`): Tweets in the default dataset. # 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": [ "apify" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dami_studio/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": ["apify"] } # Run the Actor and wait for it to finish run = client.actor("dami_studio/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": [ "apify" ] }' | apify call dami_studio/twitter-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dami_studio/twitter-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter (X) Search Scraper - Tweets by Keyword & Query", "description": "Scrape X (Twitter) search by keyword or advanced query (from:, min_faves:, filter:media, date ranges). Returns full text, engagement, author & media. Export JSON/CSV/Excel or Notion. $0.30/1k tweets - cheaper than the big providers, and failed runs are free.", "version": "0.1", "x-build-id": "rWmuVxNgLb9ezQ4rI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dami_studio~twitter-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dami_studio-twitter-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/dami_studio~twitter-search-scraper/runs": { "post": { "operationId": "runs-sync-dami_studio-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/dami_studio~twitter-search-scraper/run-sync": { "post": { "operationId": "run-sync-dami_studio-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", "properties": { "searchTerms": { "title": "Search terms", "type": "array", "description": "X search queries (advanced operators supported).", "items": { "type": "string" } }, "sort": { "title": "Sort", "enum": [ "Latest", "Top" ], "type": "string", "description": "Newest or most relevant.", "default": "Latest" }, "maxItems": { "title": "Max tweets", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Charged per tweet.", "default": 100 }, "since": { "title": "Since date", "type": "string", "description": "YYYY-MM-DD" }, "until": { "title": "Until date", "type": "string", "description": "YYYY-MM-DD" }, "onlyVerifiedUsers": { "title": "Only verified authors", "type": "boolean", "description": "Keep only verified authors.", "default": false }, "sessionCookies": { "title": "Account session cookies (required for real data)", "type": "array", "description": "X requires a logged-in session for search/lists — this is how every paid service does it. WITHOUT cookies the actor returns one clearly-labeled SAMPLE tweet (free demo mode) so you can preview the output shape. For real results add one or more throwaway-account cookies; the actor rotates them on rate-limit. From a logged-in x.com: F12 → Application → Cookies → copy auth_token and ct0. Paste each account as 'auth_token=XXXX; ct0=YYYY' (one per line).", "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Residential proxy strongly recommended (paid services use residential to protect the accounts).", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }, "notionConnector": { "title": "Notion connector ID (optional)", "type": "string", "description": "Optional Notion delivery." }, "notionParentId": { "title": "Notion data-source ID (optional)", "type": "string", "description": "Optional Notion data-source id." } } }, "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 } } } } } } } } } } ```