# 🐦 X (Twitter) Scraper βœ… $0.10/1K | Search, No API Key (`jacquemus/x-tweet-scraper`) Actor Scrape X (Twitter) by keyword/hashtag search, username, tweet URL, or ID for $0.10 per 1,000 β€” below the $0.15 market standard. Full advanced-search syntax (min\_faves, since, lang…). No X API key, no login. Full data: text, media, views, likes/reposts/replies. Retweets expanded. - **URL**: https://apify.com/jacquemus/x-tweet-scraper.md - **Developed by:** [Jacquemus](https://apify.com/jacquemus) (community) - **Categories:** Social media - **Stats:** 3 total users, 1 monthly users, 98.2% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.10 / 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. 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 ## 🐦 X (Twitter) Scraper β€” $0.10 / 1,000 tweets **Scrape X (Twitter) into clean, structured JSON β€” for a third of the usual price.** Give it a **search query**, a **username**, or **tweet links**, and get back tidy tweet records with full engagement metrics, media, and author data. No X API key, no developer account, no login β€” just results. > **$0.10 per 1,000 tweets** (market rate is ~$0.15–0.40). Pay only for what you > keep. Built on X's own endpoints over plain HTTP β€” no headless browser, so it's > fast, cheap, and reliable. --- ### ⚑ Why this scraper - πŸ’Έ **Cheapest on the Store** β€” $0.10 / 1,000 tweets, undercutting the usual $0.15–0.40 rate. No start fee, no per-query fee. - πŸ”Ž **Full X advanced search** β€” every operator works (`min_faves:`, `since:`, `from:`, `filter:media`, `lang:`, …). See the table below. - πŸ“Š **Complete engagement data** β€” likes, reposts, replies, quotes, **views**, and bookmarks on every tweet. - πŸ–ΌοΈ **Media with thumbnails** β€” image, video, and GIF URLs, plus a video **poster** image so you can preview without downloading. - πŸ” **Retweets expanded** β€” get the original tweet's full text and media, not the truncated `RT @…` shell. - πŸ€– **AI-agent ready** β€” callable as a tool from Claude, ChatGPT, Cursor, and any MCP client (see below). - πŸš€ **Fast & lightweight** β€” pure HTTP, no browser, so runs finish quickly. --- ### 🎯 What you can use it for - **Market & brand research** β€” track what people say about a product, brand, or ticker in real time. - **AI / LLM training & RAG** β€” feed fresh, structured tweets into your models, retrieval systems, and agents. - **Sentiment & trend monitoring** β€” pull the latest tweets on any topic or hashtag and run your own analysis. - **Finance & alt-data** β€” collect social signal around tickers and events for trading models. - **Lead generation & outreach** β€” find people asking about what you offer. --- ### 🧭 What you can scrape | Input | What you get | |---|---| | **Search** β€” `searchTerms` | Tweets matching a keyword/hashtag query (full advanced-search syntax) | | **User timelines** β€” `usernames` | A user's recent tweets (paginated) | | **Tweet URLs** β€” `tweetUrls` | Specific tweets by link (profile links β†’ timelines) | | **Tweet IDs** β€” `tweetIds` | Specific tweets by numeric id | Pick one mode per run. Set `searchMode` to `Latest`, `Top`, or `Media`. --- ### πŸ€– Use with AI agents (MCP) This Actor is callable by AI agents through the **Apify MCP server** β€” no extra setup. Point any MCP-capable client (Claude Desktop, ChatGPT, Cursor, or your own agent) at `https://mcp.apify.com` and just ask: > *"Search X for what people are saying about \ and summarize the sentiment."* The agent runs this Actor as a tool and streams back clean, structured tweets. --- ### πŸ“₯ Input examples **Scrape user timelines:** ```json { "usernames": ["nasa", "esa"], "maxItems": 200, "includeReplies": false } ```` **Search with advanced operators:** ```json { "searchTerms": ["artificial intelligence min_faves:100", "#nasa since:2026-01-01"], "searchMode": "Latest", "maxItems": 500, "includeSearchTerms": true } ``` ### Advanced search operators `searchTerms` is passed to X exactly as if typed into X's search box, so **every X advanced-search operator works** β€” no extra fields needed. Combine them freely: | Goal | Operator | Example | |---|---|---| | Min engagement | `min_faves:` `min_retweets:` `min_replies:` | `climate min_faves:500` | | Date range | `since:` `until:` | `nasa since:2026-01-01 until:2026-02-01` | | By / to / mentioning a user | `from:` `to:` `@` | `from:nasa filter:media` | | Language | `lang:` | `deprem lang:tr` | | Only media / images / video | `filter:media` `filter:images` `filter:videos` | `spacex filter:videos` | | Verified / Blue only | `filter:verified` `filter:blue_verified` | `ai filter:blue_verified` | | Links / news / hashtags | `filter:links` `filter:news` `filter:hashtags` | `earnings filter:news` | | A whole thread | `conversation_id:` | `conversation_id:1750000000000000001` | | Tweets from a List | `list:` | `list:123456789` | | Near a place | `near:` `within:` | `protest near:"Istanbul" within:20km` | | Exclude a term | `-` | `apple -fruit` | | Exact phrase | `"..."` | `"artificial general intelligence"` | *** ### πŸ“€ Output One tidy JSON object per tweet: ```json { "id": "2075249100035866880", "url": "https://x.com/NASA/status/2075249100035866880", "text": "July 12 will mark four years of science from @NASAWebb! …", "createdAt": "2026-07-09T16:01:56.000Z", "lang": "en", "likeCount": 216, "retweetCount": 38, "replyCount": 45, "quoteCount": 3, "viewCount": 66671, "bookmarkCount": 12, "authorUsername": "NASA", "authorFollowers": 92161445, "authorVerified": true, "imageUrls": ["https://pbs.twimg.com/media/…jpg"], "hashtags": [], "mentions": ["NASAWebb"], "isRetweet": false, "quotedTweetId": null } ``` Video and GIF tweets also carry a `poster` (cover image) alongside the playback URL in the `media` array, so you can show a thumbnail without downloading the video. Full field list in `src/types.ts`. *** ### πŸ’Έ Pricing **Pay per result** β€” $0.10 per 1,000 tweets delivered. Duplicates are removed before you're charged. No start fee, no per-query fee. Cap any run with `maxItems`. *** ### ❓ FAQ **Do I need an X API key or account?** No. Everything runs on Apify's infrastructure β€” no key, no login, no developer account. **What data does it collect?** Only **public** tweets β€” the same posts anyone can see. No private/protected accounts, no DMs. **What format is the output?** Flat JSON, exportable to CSV, Excel, JSON, or via the API β€” ready for spreadsheets, databases, and AI pipelines. **How do I control cost?** Set `maxItems` for a hard cap. You only pay per tweet delivered. **Can I search with filters?** Yes β€” every X advanced-search operator works (see the table above): engagement thresholds, dates, language, media, verified-only, and more. *** *Scrapes public data only. Please use responsibly and in line with applicable laws and X's terms.* # Actor input Schema ## `searchTerms` (type: `array`): Search X for keywords or hashtags and return matching tweets. Use this to find what people are saying about a topic in real time. Supports X advanced-search operators: min\_faves:100 (min likes), since:2026-01-01 / until: (date range), lang:en, from:username, filter:media. Example: \["AI agents min\_faves:50", "#nasa since:2026-01-01"]. Each term is searched separately. ## `searchMode` (type: `string`): Which search tab to pull from when using searchTerms. 'Latest' = most recent tweets (best for real-time monitoring), 'Top' = most engaged tweets, 'Media' = tweets with images/video. ## `usernames` (type: `array`): Scrape recent tweets from these users' timelines. Provide X handles WITHOUT the @ symbol. Use this to monitor what specific accounts are posting. Example: \["nasa", "elonmusk"]. ## `tweetUrls` (type: `array`): Fetch specific tweets by their x.com/twitter.com links (each fetched individually). Profile URLs (e.g. https://x.com/nasa) are treated as timelines. Use this when you already have the exact tweet links. ## `tweetIds` (type: `array`): Fetch specific tweets by their numeric ID (the number at the end of a tweet URL). Use this when you have raw tweet IDs rather than full links. Example: \["2075249100035866880"]. ## `maxItems` (type: `integer`): Maximum number of tweets to collect across all inputs. You are billed per tweet returned, so set this to the smallest number you need. 0 = no limit. Default 100. ## `includeReplies` (type: `boolean`): When scraping a user timeline (usernames), also include the user's replies to other people, not just their own posts. ## `includeSearchTerms` (type: `boolean`): When using searchTerms, add a 'searchTerm' field to each returned tweet showing which query produced it. Useful when searching several terms in one run. ## `proxyConfiguration` (type: `object`): Proxy settings. The default Apify datacenter proxy is enough for most requests and keeps cost low; enable residential only if you hit blocks. Leave as default unless you know you need otherwise. ## Actor input object example ```json { "searchMode": "Latest", "usernames": [ "nasa" ], "maxItems": 100, "includeReplies": false, "includeSearchTerms": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "usernames": [ "nasa" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jacquemus/x-tweet-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "usernames": ["nasa"] } # Run the Actor and wait for it to finish run = client.actor("jacquemus/x-tweet-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "usernames": [ "nasa" ] }' | apify call jacquemus/x-tweet-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jacquemus/x-tweet-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🐦 X (Twitter) Scraper βœ… $0.10/1K | Search, No API Key", "description": "Scrape X (Twitter) by keyword/hashtag search, username, tweet URL, or ID for $0.10 per 1,000 β€” below the $0.15 market standard. Full advanced-search syntax (min_faves, since, lang…). No X API key, no login. Full data: text, media, views, likes/reposts/replies. Retweets expanded.", "version": "0.1", "x-build-id": "AZ9Rxr5R3qhBLW271" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jacquemus~x-tweet-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jacquemus-x-tweet-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/jacquemus~x-tweet-scraper/runs": { "post": { "operationId": "runs-sync-jacquemus-x-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/jacquemus~x-tweet-scraper/run-sync": { "post": { "operationId": "run-sync-jacquemus-x-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", "properties": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Search X for keywords or hashtags and return matching tweets. Use this to find what people are saying about a topic in real time. Supports X advanced-search operators: min_faves:100 (min likes), since:2026-01-01 / until: (date range), lang:en, from:username, filter:media. Example: [\"AI agents min_faves:50\", \"#nasa since:2026-01-01\"]. Each term is searched separately.", "items": { "type": "string" } }, "searchMode": { "title": "Search mode", "enum": [ "Latest", "Top", "Media" ], "type": "string", "description": "Which search tab to pull from when using searchTerms. 'Latest' = most recent tweets (best for real-time monitoring), 'Top' = most engaged tweets, 'Media' = tweets with images/video.", "default": "Latest" }, "usernames": { "title": "Usernames / handles", "type": "array", "description": "Scrape recent tweets from these users' timelines. Provide X handles WITHOUT the @ symbol. Use this to monitor what specific accounts are posting. Example: [\"nasa\", \"elonmusk\"].", "items": { "type": "string" } }, "tweetUrls": { "title": "Tweet or profile URLs", "type": "array", "description": "Fetch specific tweets by their x.com/twitter.com links (each fetched individually). Profile URLs (e.g. https://x.com/nasa) are treated as timelines. Use this when you already have the exact tweet links.", "items": { "type": "string" } }, "tweetIds": { "title": "Tweet IDs", "type": "array", "description": "Fetch specific tweets by their numeric ID (the number at the end of a tweet URL). Use this when you have raw tweet IDs rather than full links. Example: [\"2075249100035866880\"].", "items": { "type": "string" } }, "maxItems": { "title": "Max tweets", "minimum": 0, "type": "integer", "description": "Maximum number of tweets to collect across all inputs. You are billed per tweet returned, so set this to the smallest number you need. 0 = no limit. Default 100.", "default": 100 }, "includeReplies": { "title": "Include replies in timelines", "type": "boolean", "description": "When scraping a user timeline (usernames), also include the user's replies to other people, not just their own posts.", "default": false }, "includeSearchTerms": { "title": "Tag results with their search term", "type": "boolean", "description": "When using searchTerms, add a 'searchTerm' field to each returned tweet showing which query produced it. Useful when searching several terms in one run.", "default": false }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Proxy settings. The default Apify datacenter proxy is enough for most requests and keeps cost low; enable residential only if you hit blocks. Leave as default unless you know you need otherwise.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```