# LinkedIn Posts Scraper (No Cookies) (`peach_junior/linkedin-posts-scraper`) Actor Extract post content, author details, engagement metrics, media, and comments from public LinkedIn posts. No login or cookies required. Perfect for brand monitoring, content analysis, and competitor research. - **URL**: https://apify.com/peach\_junior/linkedin-posts-scraper.md - **Developed by:** [Or Broski](https://apify.com/peach_junior) (community) - **Categories:** Lead generation, Social media, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## LinkedIn Posts Scraper (No Cookies) Extract post content, author details, engagement metrics, and media from **public LinkedIn posts** — no login, no cookies, no account risk. ### Features - **No authentication required** — scrapes public post pages, zero risk to your LinkedIn account - **8 fallback selectors** — extracts data even when LinkedIn changes its DOM - **Engagement metrics** — comment counts, reaction counts, pre-computed `engagement_total` - **Post type detection** — text_only, text_with_image, video, image_only - **Retry with backoff** — automatically retries rate-limited posts up to 3× - **Residential proxies** — uses Apify's built-in residential proxy pool to avoid blocks - **MCP-ready** — structured JSON output works with AI agents and automation tools ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `postUrls` | Array | Yes | List of LinkedIn post URLs to scrape | | `includeComments` | Boolean | No | Extract comments (default: `false`) | | `maxCommentsPerPost` | Number | No | Max comments per post (default: `20`) | | `includeMedia` | Boolean | No | Extract image/video URLs (default: `true`) | | `maxPosts` | Number | No | Limit total posts (0 = unlimited) | | `proxyConfiguration` | Object | No | Proxy settings (residential recommended) | #### Example Input ```json { "postUrls": [ { "url": "https://www.linkedin.com/posts/satyanadella_ai-copilot-activity-123456" }, { "url": "https://www.linkedin.com/posts/company_announcement-activity-789012" } ], "includeComments": false, "includeMedia": true } ```` ### Output Each post returns: ```json { "post_id": "urn:li:activity:7373381341473787905", "post_url": "https://www.linkedin.com/posts/...", "author": { "name": "S. Somasegar", "headline": "Managing Director at Madrona Ventures", "profile_url": "https://www.linkedin.com/in/s-somasegar-113791a5" }, "content": { "text": "No one would ever say it's easy to be in Satya Nadella's shoes...", "hashtags": [], "links": ["https://lnkd.in/gf5cCaSN"] }, "engagement": { "reactions": 18, "comments": 13, "engagement_total": 31 }, "metadata": { "posted_at": "2025-05-15T14:30:00Z", "visibility": "public", "is_repost": false, "post_type": "text_only" }, "media": [], "scraped_at": "2026-07-08T18:33:01Z" } ``` ### Use Cases - **Brand monitoring** — track what people are saying about your company - **Content analysis** — study competitor content strategy and engagement - **Lead research** — analyze posts from prospects before outreach - **Influencer tracking** — monitor thought leaders in your industry - **AI training data** — build datasets of professional content with engagement signals ### Limitations - **Public posts only** — posts visible to "Connections only" or "Private" cannot be scraped - **No login** — richer data (skills, experience, full reactions breakdown) requires authenticated mode (coming in v2) - **Rate limits** — LinkedIn may throttle high-volume scraping. The actor automatically retries with backoff. - **Selectors may break** — LinkedIn changes its HTML periodically. This actor uses multiple fallback selectors but may need updates. ### Pricing This actor is currently **free** while in beta. Commercial pricing (Pay Per Event) coming soon. ### Support Found a bug? Have a feature request? [Open an issue](https://apify.com/peach_junior/linkedin-posts-scraper/issues). *** Built with [Apify SDK](https://docs.apify.com/sdk/python) + [Playwright](https://playwright.dev) + stealth anti-detection. # Actor input Schema ## `postUrls` (type: `array`): URLs of LinkedIn posts to scrape ## `profileUrls` (type: `array`): URLs of LinkedIn profiles to scrape (e.g. https://www.linkedin.com/in/username/) ## `includeComments` (type: `boolean`): If true, scrape comments on each post ## `maxCommentsPerPost` (type: `integer`): Maximum number of comments to scrape per post (only if includeComments is true) ## `includeMedia` (type: `boolean`): If true, extract image and video URLs from posts ## `maxPosts` (type: `integer`): Maximum number of posts to scrape. 0 = no limit ## `proxyConfiguration` (type: `object`): Proxy settings for the scraper. Using residential proxies is strongly recommended for LinkedIn. ## Actor input object example ```json { "postUrls": [ { "url": "https://www.linkedin.com/posts/username_post-id" } ], "profileUrls": [ { "url": "https://www.linkedin.com/in/williamhgates/" } ], "includeComments": false, "maxCommentsPerPost": 20, "includeMedia": true, "maxPosts": 0, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "postUrls": [ { "url": "https://www.linkedin.com/posts/username_post-id" } ], "profileUrls": [ { "url": "https://www.linkedin.com/in/williamhgates/" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("peach_junior/linkedin-posts-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 = { "postUrls": [{ "url": "https://www.linkedin.com/posts/username_post-id" }], "profileUrls": [{ "url": "https://www.linkedin.com/in/williamhgates/" }], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("peach_junior/linkedin-posts-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 '{ "postUrls": [ { "url": "https://www.linkedin.com/posts/username_post-id" } ], "profileUrls": [ { "url": "https://www.linkedin.com/in/williamhgates/" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call peach_junior/linkedin-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=peach_junior/linkedin-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Posts Scraper (No Cookies)", "description": "Extract post content, author details, engagement metrics, media, and comments from public LinkedIn posts. No login or cookies required. Perfect for brand monitoring, content analysis, and competitor research.", "version": "0.2", "x-build-id": "29cPPghYj2IXgroHd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/peach_junior~linkedin-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-peach_junior-linkedin-posts-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/peach_junior~linkedin-posts-scraper/runs": { "post": { "operationId": "runs-sync-peach_junior-linkedin-posts-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/peach_junior~linkedin-posts-scraper/run-sync": { "post": { "operationId": "run-sync-peach_junior-linkedin-posts-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": { "postUrls": { "title": "LinkedIn Post URLs", "type": "array", "description": "URLs of LinkedIn posts to scrape", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "profileUrls": { "title": "LinkedIn Profile URLs", "type": "array", "description": "URLs of LinkedIn profiles to scrape (e.g. https://www.linkedin.com/in/username/)", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "If true, scrape comments on each post", "default": false }, "maxCommentsPerPost": { "title": "Max Comments Per Post", "minimum": 0, "maximum": 100, "type": "integer", "description": "Maximum number of comments to scrape per post (only if includeComments is true)", "default": 20 }, "includeMedia": { "title": "Include Media URLs", "type": "boolean", "description": "If true, extract image and video URLs from posts", "default": true }, "maxPosts": { "title": "Max Posts", "minimum": 0, "type": "integer", "description": "Maximum number of posts to scrape. 0 = no limit", "default": 0 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the scraper. Using residential proxies is strongly recommended for LinkedIn." } } }, "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 } } } } } } } } } } ```