Pricing
Pay per event
🚀 Harness the full power of X (Twitter) Advanced Search! Filter by keywords, users, dates, engagement & more. Fast, stable, and precise data.
0.0 (0)
Pricing
Pay per event
1
11
8
Last modified
8 days ago
You can access the Ultimate X (Twitter) Advanced Search Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "gytbw9KvfJX3HQbPl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delicious_zebu~ultimate-x-twitter-advanced-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delicious_zebu-ultimate-x-twitter-advanced-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delicious_zebu~ultimate-x-twitter-advanced-search-scraper/runs": { "post": { "operationId": "runs-sync-delicious_zebu-ultimate-x-twitter-advanced-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delicious_zebu~ultimate-x-twitter-advanced-search-scraper/run-sync": { "post": { "operationId": "run-sync-delicious_zebu-ultimate-x-twitter-advanced-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startDate", "endDate", "splitMode", "language" ], "properties": { "startDate": { "title": "Start Date (YYYY-MM-DD)", "type": "string", "description": "Start date (inclusive). Format: YYYY-MM-DD.", "default": "2025-10-01" }, "endDate": { "title": "End Date (YYYY-MM-DD)", "type": "string", "description": "End date (inclusive). Format: YYYY-MM-DD.", "default": "2025-10-31" }, "splitMode": { "title": "Split Mode", "enum": [ "day", "week", "month" ], "type": "string", "description": "How to split the date range into segments: day, week or month.", "default": "day" }, "language": { "title": "Language", "enum": [ "any", "ar", "ar-x-fm", "bn", "eu", "bg", "ca", "hr", "cs", "da", "nl", "en", "fi", "fr", "de", "el", "gu", "he", "hi", "hu", "id", "it", "ja", "kn", "ko", "mr", "no", "fa", "pl", "pt", "ro", "ru", "sr", "zh-cn", "sk", "es", "sv", "ta", "th", "zh-tw", "tr", "uk", "ur", "vi" ], "type": "string", "description": "Language filter for search. Use 'any' to disable filtering.", "default": "any" }, "maxItems": { "title": "Max Items", "minimum": 0, "type": "integer", "description": "Maximum number of tweets to collect. 0 means unlimited.", "default": 80 }, "All_of_these_words": { "title": "All of these words", "type": "string", "description": "Tweets must contain all these words (space-separated).", "default": "ai" }, "This_exact_phrase": { "title": "This exact phrase", "type": "string", "description": "Tweets must contain this exact phrase.", "default": "" }, "Any_of_these_words": { "title": "Any of these words", "type": "string", "description": "Tweets containing any of these words (space-separated) will match.", "default": "" }, "None_of_these_words": { "title": "None of these words", "type": "string", "description": "Exclude tweets containing these words (space-separated).", "default": "" }, "These_hashtags": { "title": "These hashtags", "type": "string", "description": "Hashtags without #, space-separated. Example: nasa spacex", "default": "" }, "From_these_accounts": { "title": "From these accounts", "type": "string", "description": "Space-separated screen names without @. Example: elonmusk NASA", "default": "elonmusk" }, "To_these_accounts": { "title": "To these accounts", "type": "string", "description": "Space-separated screen names without @.", "default": "" }, "Mentioning_these_accounts": { "title": "Mentioning these accounts", "type": "string", "description": "Space-separated screen names without @.", "default": "" }, "Minimum_replies": { "title": "Minimum replies", "minimum": 0, "type": "integer", "description": "Only include tweets with at least this many replies.", "default": 0 }, "Minimum_likes": { "title": "Minimum likes", "minimum": 0, "type": "integer", "description": "Only include tweets with at least this many likes.", "default": 0 }, "Minimum_reposts": { "title": "Minimum reposts", "minimum": 0, "type": "integer", "description": "Only include tweets with at least this many reposts (retweets + quotes).", "default": 0 } } }, "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 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Ultimate X (Twitter) Advanced Search Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
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