# X (Twitter) Article to Markdown Scraper - Long Form Posts (`seemuapps/x-article-to-markdown-scraper`) Actor Convert any X (Twitter) long-form Article or Notes post into clean Markdown, ready for AI, RAG, and LLM ingestion pipelines. - **URL**: https://apify.com/seemuapps/x-article-to-markdown-scraper.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Social media, Developer tools, Lead generation - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 article 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) Article to Markdown Scraper - Long Form Posts Convert any X (Twitter) long-form Article or Notes post into clean Markdown, ready for AI, RAG, and LLM ingestion pipelines. ### What you get - Full article body converted to clean, structured Markdown - headings, lists, bold/italic/code, images, and dividers all preserved - Title and byline prepended to the Markdown so every record is a self-contained document - Cover image URL and preview text for quick previews or thumbnails - Author details - username, display name, verification status, follower count - Engagement stats - replies, likes, quotes, views - One dataset row per article - batch convert a whole list of IDs or URLs in a single run ### Free tier vs. paid Free runs are capped to help cover data costs (this endpoint is pricier than a standard tweet lookup): - **10 articles per run** - **3 runs per day** (UTC) - **30-minute wait** between runs Upgrade to any paid plan on the actor's pricing page to lift all three limits - your `Max Articles` setting is honored in full and runs are unrestricted. ### Use cases - Feed long-form X Articles into a RAG pipeline or LLM knowledge base - Content archiving - keep a durable Markdown copy of Articles before they're edited or deleted - Newsletter curation - pull Article bodies straight into a Markdown-based editor - Competitive content research - track what long-form content competitors and creators are publishing - AI agent tool input - give an agent clean Markdown instead of raw HTML or JSON ### How to use 1. Enter one or more **Article / Tweet IDs or URLs** (numeric IDs or `https://x.com/user/status/...` links) - only posts published via X's Article/Notes feature will convert; regular tweets are skipped 2. Set **Max Articles** (default 10; 0 for unlimited, capped to the number of IDs supplied) 3. Run the actor - one Markdown document per row in the **Dataset** tab 4. Copy the `markdown` field straight into your pipeline, CMS, or knowledge base ### Output format One article per dataset row: ```json { "tweetId": "1905545699552375179", "title": "Why Long-Form Publishing Is Coming Back", "markdown": "# Why Long-Form Publishing Is Coming Back\n\n*by @exampleauthor*\n\nShort platform posts are great for reach, but they flatten nuance...\n\n## The case for depth\n\n- Readers retain more from structured, longer pieces\n- Search and AI systems reward well-organized content\n\n> The best ideas need room to breathe.", "previewText": "Short platform posts are great for reach, but they flatten nuance...", "coverImageUrl": "https://pbs.twimg.com/media/example.jpg", "authorUsername": "exampleauthor", "authorName": "Example Author", "authorIsBlueVerified": true, "authorFollowersCount": 184200, "createdAt": "Wed Mar 27 14:02:00 +0000 2026", "replyCount": 312, "likeCount": 9840, "quoteCount": 118, "viewCount": 512000, "articleUrl": "https://x.com/exampleauthor/status/1905545699552375179" } ```` ### Input options | Field | Type | Description | |-------|------|-------------| | Article / Tweet IDs or URLs | array of strings | Numeric IDs or full tweet URLs to convert (required, at least one) | | Max Articles | integer | Cap on how many articles get fetched and converted this run - default 10, 0 for unlimited | ### Related X (Twitter) actors Part of a complete X (Twitter) toolkit - explore the rest of the suite: - [X (Twitter) Profile Scraper](https://apify.com/seemuapps/x-profile-scraper) - Public profile data - bio, counts, links - [X (Twitter) User Tweets Scraper](https://apify.com/seemuapps/x-user-tweets-by-username) - Full timeline of any account by username - [X (Twitter) Tweet Scraper](https://apify.com/seemuapps/x-tweet-scraper) - Search and export tweets by query, hashtag, user - [X (Twitter) Tweet Replies Scraper](https://apify.com/seemuapps/x-tweet-replies-scraper) - Every reply under a post for sentiment analysis - [X (Twitter) Quote Tweets Scraper](https://apify.com/seemuapps/x-quote-tweets-scraper) - Every quote tweet of a post, with engagement - [X (Twitter) Followers & Following Scraper](https://apify.com/seemuapps/x-followers-following-scraper) - Full followers and following lists, no login - [X (Twitter) List Members Scraper](https://apify.com/seemuapps/x-list-members-scraper) - Members or followers of any public list - [X (Twitter) Active Hours Analyzer](https://apify.com/seemuapps/x-active-hours-analyzer) - Posting heatmap, peak hours, and time zone - [X (Twitter) Retweeters Scraper](https://apify.com/seemuapps/x-tweet-retweeters-scraper) - Find every account that retweeted a post - [X (Twitter) User Mentions Scraper](https://apify.com/seemuapps/x-user-mentions-scraper) - Brand and keyword monitoring across mentions - [X (Twitter) User Search Scraper](https://apify.com/seemuapps/x-user-search-scraper) - Find accounts by bio or keyword for lead gen - [X (Twitter) Trends Scraper](https://apify.com/seemuapps/x-trends-scraper) - Trending topics and hashtags by location - [X (Twitter) MCP Server](https://apify.com/seemuapps/x-mcp) - All X tools for AI agents via MCP # Actor input Schema ## `tweetIds` (type: `array`): List of X (Twitter) Article/Notes tweet IDs (numeric) or full tweet URLs (https://x.com/user/status/) to convert to Markdown. Regular (non-Article) tweets are skipped. ## `maxItems` (type: `integer`): Maximum number of articles to fetch and convert this run. Set 0 for unlimited (up to the length of the input list). ## Actor input object example ```json { "tweetIds": [ "1905545699552375179" ], "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): One row per article: tweetId, title, markdown (the full converted Markdown body, including title and byline), previewText, coverImageUrl, author info, engagement counts, and articleUrl. # 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": [ "1905545699552375179" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/x-article-to-markdown-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": ["1905545699552375179"] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/x-article-to-markdown-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": [ "1905545699552375179" ] }' | apify call seemuapps/x-article-to-markdown-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/x-article-to-markdown-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X (Twitter) Article to Markdown Scraper - Long Form Posts", "description": "Convert any X (Twitter) long-form Article or Notes post into clean Markdown, ready for AI, RAG, and LLM ingestion pipelines.", "version": "1.0", "x-build-id": "0DROWFn5oHm6A4c4t" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~x-article-to-markdown-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-x-article-to-markdown-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~x-article-to-markdown-scraper/runs": { "post": { "operationId": "runs-sync-seemuapps-x-article-to-markdown-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~x-article-to-markdown-scraper/run-sync": { "post": { "operationId": "run-sync-seemuapps-x-article-to-markdown-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Article / Tweet IDs or URLs", "type": "array", "description": "List of X (Twitter) Article/Notes tweet IDs (numeric) or full tweet URLs (https://x.com/user/status/) to convert to Markdown. Regular (non-Article) tweets are skipped.", "items": { "type": "string" } }, "maxItems": { "title": "Max Articles", "minimum": 0, "type": "integer", "description": "Maximum number of articles to fetch and convert this run. Set 0 for unlimited (up to the length of the input list).", "default": 10 } } }, "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 } } } } } } } } } } ```