# Free Tweet Scraper (`coder_luffy/free-tweet-scraper`) Actor Extract full details from any public Tweet (now X post) using just the Tweet ID — no login, API key, or authentication required. Just input one or more Tweet IDs, and this actor will return clean, JSON-formatted results ready for analysis or integration. - **URL**: https://apify.com/coder\_luffy/free-tweet-scraper.md - **Developed by:** [Luffy](https://apify.com/coder_luffy) (community) - **Categories:** Social media, Other - **Stats:** 279 total users, 0 monthly users, 100.0% runs succeeded, 27 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $4.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Free Tweet Scraper - Twitter/X API (100% Free) ![logo of Tweet Scraper](https://i.imgur.com/mduMotb.png) **Actor URL**: [coder_luffy/free-tweet-scraper](https://apify.com/coder_luffy/free-tweet-scraper) ### Overview This free Tweet Scraper lets you extract **detailed data from tweets using Tweet IDs**. Whether you're a **developer**, **researcher**, **data analyst**, or **crypto/NFT marketer**, this API gives you clean, structured JSON for deeper Twitter (X) insight. Unlike other premium APIs, this one is **completely free to use** and doesn't require official API keys. --- ### Input ```json { "tweetIds": [ "1806763776881860918", "1911772010193002581" ] } ```` ## You can send one or multiple Tweet IDs in the `tweetIds` array. ### ✅ Features & Output Summary - **Tweet ID** - **Language** - **Text content** - **Creation date** - **Favorite count** - **Conversation count** - **Tweet sensitivity** - **Hashtags** - **User info (name, screen name, image, verification)** - **Photo/media info (URLs, dimensions, file size)** - **Quoted tweet details (if any)** *** ### Output JSON (Example Response) ```json [ { "tweet_id": "1806763776881860918", "lang": "en", "favorite_count": 1008, "possibly_sensitive": false, "created_at": "2024-06-28T18:57:07.000Z", "display_text_range": [0, 41], "entities": { "hashtags": [ { "indices": [6, 15], "text": "memecoin" }, { "indices": [23, 29], "text": "1000x" } ], "urls": [], "user_mentions": [], "symbols": [], "media": [ { "display_url": "pic.x.com/yy7vzY4XY6", "expanded_url": "https://x.com/elonmuskdoge69/status/1806763776881860918/photo/1", "indices": [42, 65], "url": "https://t.co/yy7vzY4XY6" } ] }, "id_str": "1806763776881860918", "text": "Which #memecoin can do #1000x this year? https://t.co/yy7vzY4XY6", "user": { "id_str": "285203751", "name": "Elon Musk (Parody)", "profile_image_url_https": "https://pbs.twimg.com/profile_images/1749541403364147200/Em6jSVfl_normal.jpg", "screen_name": "elonmuskdoge69", "verified": false, "is_blue_verified": true, "profile_image_shape": "Circle" }, "mediaDetails": [ { "display_url": "pic.x.com/yy7vzY4XY6", "expanded_url": "https://x.com/elonmuskdoge69/status/1806763776881860918/photo/1", "ext_media_availability": { "status": "Available" }, "indices": [42, 65], "media_url_https": "https://pbs.twimg.com/media/GRLqDuaWgAAUiba.jpg", "original_info": { "height": 543, "width": 411 }, "sizes": { "large": { "h": 543, "resize": "fit", "w": 411 }, "medium": { "h": 543, "resize": "fit", "w": 411 }, "small": { "h": 543, "resize": "fit", "w": 411 }, "thumb": { "h": 150, "resize": "crop", "w": 150 } }, "type": "photo", "url": "https://t.co/yy7vzY4XY6" } ], "photos": [ { "backgroundColor": { "red": 204, "green": 214, "blue": 221 }, "expandedUrl": "https://x.com/elonmuskdoge69/status/1806763776881860918/photo/1", "url": "https://pbs.twimg.com/media/GRLqDuaWgAAUiba.jpg", "width": 411, "height": 543 } ], "conversation_count": 1118, "news_action_type": "conversation", "error": false, "details": "successfully retrieved the tweet." }, { "tweet_id": "1911772010193002581", "lang": "en", "favorite_count": 44337, "created_at": "2025-04-14T13:22:20.000Z", "display_text_range": [0, 38], "entities": { "hashtags": [], "urls": [], "user_mentions": [], "symbols": [] }, "id_str": "1911772010193002581", "text": "Tesla full self-driving will amaze you", "user": { "id_str": "44196397", "name": "Elon Musk", "profile_image_url_https": "https://pbs.twimg.com/profile_images/1893803697185910784/Na5lOWi5_normal.jpg", "screen_name": "elonmusk", "verified": false, "highlighted_label": { "description": "X", "badge": { "url": "https://pbs.twimg.com/profile_images/1683899100922511378/5lY42eHs_bigger.jpg" }, "url": { "url": "https://twitter.com/X", "url_type": "DeepLink" }, "user_label_type": "BusinessLabel", "user_label_display_type": "Badge" }, "is_blue_verified": true }, "conversation_count": 4438, "news_action_type": "conversation", "quoted_tweet": { "lang": "en", "reply_count": 377, "retweet_count": 130, "favorite_count": 1448, "possibly_sensitive": false, "created_at": "2025-04-14T05:26:30.000Z", "display_text_range": [0, 71], "entities": { "hashtags": [], "urls": [], "user_mentions": [], "symbols": [], "media": [ { "display_url": "pic.x.com/ZgNc2b5wMY", "expanded_url": "https://x.com/SawyerMerritt/status/1911652259735142842/photo/1", "indices": [72, 95], "url": "https://t.co/ZgNc2b5wMY" } ] }, "id_str": "1911652259735142842", "text": "44% of voters have not tried any version of Tesla FSD (Supervised) V13. https://t.co/ZgNc2b5wMY", "user": { "id_str": "243013409", "name": "Sawyer Merritt", "profile_image_url_https": "https://pbs.twimg.com/profile_images/1837744842715082752/xH9vYixL_normal.jpg", "screen_name": "SawyerMerritt", "verified": false, "is_blue_verified": true, "profile_image_shape": "Circle" }, "mediaDetails": [ { "display_url": "pic.x.com/ZgNc2b5wMY", "expanded_url": "https://x.com/SawyerMerritt/status/1911652259735142842/photo/1", "ext_media_availability": { "status": "Available" }, "indices": [72, 95], "media_url_https": "https://pbs.twimg.com/media/GoeNaJIXcAAP3fI.jpg", "original_info": { "height": 598, "width": 1388 }, "sizes": { "large": { "h": 598, "resize": "fit", "w": 1388 }, "medium": { "h": 517, "resize": "fit", "w": 1200 }, "small": { "h": 293, "resize": "fit", "w": 680 }, "thumb": { "h": 150, "resize": "crop", "w": 150 } }, "type": "photo", "url": "https://t.co/ZgNc2b5wMY" } ], "photos": [ { "backgroundColor": { "red": 204, "green": 214, "blue": 221 }, "expandedUrl": "https://x.com/SawyerMerritt/status/1911652259735142842/photo/1", "url": "https://pbs.twimg.com/media/GoeNaJIXcAAP3fI.jpg", "width": 1388, "height": 598 } ], "isEdited": false, "isStaleEdit": false }, "error": false, "details": "successfully retrieved the tweet." } ] ``` *** ### Use Cases - Twitter/X data analysis - Social media monitoring - Crypto/NFT trend tracking - Marketing research - Sentiment and engagement analysis - Media archiving *** ### 100% Free Unlike many tools, this Tweet Scraper is completely **free** to use and doesn’t need an official API token. You can scrape tweet details instantly without signing up for a paid developer plan. *** ## Made with ❤️ by [Coder Luffy](https://apify.com/coder_luffy) **Free Tweet Scraper**, **Twitter API alternative**, **X.com tweet data extractor**, **Tweet ID to JSON**, **scrape tweet details**, **Twitter sentiment analysis tool**, **media data from tweet**, **tweet metadata parser**, **no API key Twitter scraper**, **free Twitter API for developers** # Actor input Schema ## `tweetIds` (type: `array`): Enter the list of Tweet IDs to extract their corresponding Tweet details. ## Actor input object example ```json { "tweetIds": [ "1806763776881860918", "1911772010193002581" ] } ``` # 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 = { "tweetIds": [ "1806763776881860918", "1911772010193002581" ] }; // Run the Actor and wait for it to finish const run = await client.actor("coder_luffy/free-tweet-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 = { "tweetIds": [ "1806763776881860918", "1911772010193002581", ] } # Run the Actor and wait for it to finish run = client.actor("coder_luffy/free-tweet-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 '{ "tweetIds": [ "1806763776881860918", "1911772010193002581" ] }' | apify call coder_luffy/free-tweet-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=coder_luffy/free-tweet-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Free Tweet Scraper", "description": "Extract full details from any public Tweet (now X post) using just the Tweet ID — no login, API key, or authentication required.\n\nJust input one or more Tweet IDs, and this actor will return clean, JSON-formatted results ready for analysis or integration.", "version": "0.0", "x-build-id": "QA2d4tVwOFNnWAj1B" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/coder_luffy~free-tweet-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-coder_luffy-free-tweet-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/coder_luffy~free-tweet-scraper/runs": { "post": { "operationId": "runs-sync-coder_luffy-free-tweet-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/coder_luffy~free-tweet-scraper/run-sync": { "post": { "operationId": "run-sync-coder_luffy-free-tweet-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "tweetIds" ], "properties": { "tweetIds": { "title": "Tweet IDs", "type": "array", "description": "Enter the list of Tweet IDs to extract their corresponding Tweet details.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```