# Markdown to X (Twitter) Article Publisher 2026 (`fastcrawler/markdown-to-x-twitter-article-publisher-2026`) Actor Convert and publish Markdown content directly into X long-form Articles. Automate your writing and publishing workflow seamlessly without needing a Twitter developer account or official API access. - **URL**: https://apify.com/fastcrawler/markdown-to-x-twitter-article-publisher-2026.md - **Developed by:** [fastcrawler](https://apify.com/fastcrawler) (community) - **Categories:** Social media, AI, Agents - **Stats:** 2 total users, 1 monthly users, 76.5% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 1,000 postxarticles This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Markdown to X (Twitter) Article Publisher An advanced automation tool designed to publish rich Markdown documents directly into **X (Twitter) Articles** (long-form content). Streamline your publishing workflow from your headless CMS, local files, or AI Agents straight to X—**completely bypassing the need for an expensive official Twitter API subscription or developer account.** --- ### 🚀 Key Features 1. **Direct Markdown Rendering:** Seamlessly converts your standard Markdown format (headings, bold text, bullet points, links) into fully formatted X Articles. 2. **No Twitter API Required:** Operates via account session cookies, saving you from complex approval processes and costly official API tiers. 3. **Visibility Control:** Fully supports setting article visibility to Public, Followers, or Mentioned users directly from the input. 4. **Built for Automation & AI Agents:** Easily integrate this Actor into your existing tech stack, CI/CD pipelines, Make/Zapier workflows, or LLM-based autonomous agents. --- ### ⚙️ Input Parameters | Field | Type | Required / Default | Description | | :--- | :--- | :--- | :--- | | `cookie` | String | **Required** | Twitter cookie string (e.g., `auth_token=...; ct0=...; twid=...`). Used to authorize the actor with X. | | `title` | String | **Required** | The main headline/title for your X Article. | | `markdown` | String | **Required** | The raw Markdown text content you want to publish as the article body. | | `cover_image` | String | Optional (null) | Cover image URL (https) or local file path to display at the top of your article. | | `visibility` | String | Default: `Public` | Set who can view the article. Options: `Public` / `Followers` / `Mentioned`. | --- ### 📊 Output Data After a successful run, the Actor outputs the results directly into the default Apify Dataset in a clean JSON format containing the following identifiers: ```json { "article_id": "1895304729104826368", "tweet_id": "1895304731554627584" } ### 🛠️ Quick Start 1. **Get your Cookie:** Log into your X account in your browser, open Developer Tools (F12) or use an extension like *EditThisCookie*, and copy the cookie string containing `auth_token`, `ct0`, etc. 2. **Set up Input:** Paste your cookie string into the `cookie` field, write your `title`, and add your article body in the `markdown` field. 3. **Run the Actor:** Click **Run**. Your formatted long-form article will be live on X in seconds! --- ### 📬 Contact & Feature Requests If you need customized features, enterprise-scale scraping solutions, or technical support, feel free to reach out: * 📧 **Email:** fastcrawler9@gmail.com * 💬 **Telegram:** [Join Chat](https://t.me/+MUMR3PKOoVVjNzE9) * 🎮 **Discord:** [Join Server](https://discord.gg/s4jyupzaWu) #### 💡 Check Out Our Other Tools: * 🌐 **[Free Twitter API](https://twexapi.io):** Affordable, robust third-party X data and crawling API. * 📈 **[Track X Influencers Tweets in Real-time](https://xmonitor.online):** Monitor key accounts and trends with zero latency. # Actor input Schema ## `cookie` (type: `string`): Twitter cookie string (e.g., auth_token=...; ct0=...; twid=...). Used to authorize the actor with X. ## `title` (type: `string`): The headline or title for your X Article. ## `markdown` (type: `string`): Article body content in standard Markdown format. ## `cover_image` (type: `string`): Cover image: https URL or local file path (optional). ## `visibility` (type: `string`): Who can view this article on X. ## Actor input object example ```json { "cookie": "auth_token=xxxx; ct0=xxxx;", "title": "My Awesome Long-form Article", "markdown": "# Mastering X Long-Form Articles\n\nThis is the **bold** body text demonstrating how seamlessly your standard Markdown syntax renders directly into an X Article.\n\n![Demo Image](https://images.unsplash.com/photo-1618005182384-a83a8bd57fbe?w=800)", "visibility": "Public" } ```` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "cookie": "auth_token=xxxx; ct0=xxxx;", "title": "My Awesome Long-form Article", "markdown": `# Mastering X Long-Form Articles This is the **bold** body text demonstrating how seamlessly your standard Markdown syntax renders directly into an X Article. ![Demo Image](https://images.unsplash.com/photo-1618005182384-a83a8bd57fbe?w=800)` }; // Run the Actor and wait for it to finish const run = await client.actor("fastcrawler/markdown-to-x-twitter-article-publisher-2026").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 = { "cookie": "auth_token=xxxx; ct0=xxxx;", "title": "My Awesome Long-form Article", "markdown": """# Mastering X Long-Form Articles This is the **bold** body text demonstrating how seamlessly your standard Markdown syntax renders directly into an X Article. ![Demo Image](https://images.unsplash.com/photo-1618005182384-a83a8bd57fbe?w=800)""", } # Run the Actor and wait for it to finish run = client.actor("fastcrawler/markdown-to-x-twitter-article-publisher-2026").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 '{ "cookie": "auth_token=xxxx; ct0=xxxx;", "title": "My Awesome Long-form Article", "markdown": "# Mastering X Long-Form Articles\\n\\nThis is the **bold** body text demonstrating how seamlessly your standard Markdown syntax renders directly into an X Article.\\n\\n![Demo Image](https://images.unsplash.com/photo-1618005182384-a83a8bd57fbe?w=800)" }' | apify call fastcrawler/markdown-to-x-twitter-article-publisher-2026 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fastcrawler/markdown-to-x-twitter-article-publisher-2026", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Markdown to X (Twitter) Article Publisher 2026", "description": "Convert and publish Markdown content directly into X long-form Articles. Automate your writing and publishing workflow seamlessly without needing a Twitter developer account or official API access.", "version": "0.0", "x-build-id": "hmUbw23uDWNblUpgp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fastcrawler~markdown-to-x-twitter-article-publisher-2026/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fastcrawler-markdown-to-x-twitter-article-publisher-2026", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fastcrawler~markdown-to-x-twitter-article-publisher-2026/runs": { "post": { "operationId": "runs-sync-fastcrawler-markdown-to-x-twitter-article-publisher-2026", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fastcrawler~markdown-to-x-twitter-article-publisher-2026/run-sync": { "post": { "operationId": "run-sync-fastcrawler-markdown-to-x-twitter-article-publisher-2026", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "cookie", "title", "markdown" ], "properties": { "cookie": { "title": "Twitter Cookie", "type": "string", "description": "Twitter cookie string (e.g., auth_token=...; ct0=...; twid=...). Used to authorize the actor with X." }, "title": { "title": "Article Title", "type": "string", "description": "The headline or title for your X Article." }, "markdown": { "title": "Markdown Body", "type": "string", "description": "Article body content in standard Markdown format." }, "cover_image": { "title": "Cover Image", "type": "string", "description": "Cover image: https URL or local file path (optional)." }, "visibility": { "title": "Visibility", "enum": [ "Public", "Followers", "Mentioned" ], "type": "string", "description": "Who can view this article on X.", "default": "Public" } } }, "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 } } } } } } } } } } ```