# Get Post Details (`freshdata/get-post-details`) Actor The **Get Post Details** is a powerful tool designed to extract detailed reactions data from any profile posts — without the need for cookies or login. - **URL**: https://apify.com/freshdata/get-post-details.md - **Developed by:** [FreshData](https://apify.com/freshdata) (community) - **Categories:** Lead generation, Social media - **Stats:** 155 total users, 148 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $8.00 / 1,000 processing data 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 ## 🚀 LinkedIn Post's Details Scraper The **Linkedin Post's Details Scraper** is a powerful tool designed to extract detailed reactions data from any profile posts — without the need for cookies or login. ### ✨ Features - 👤 **Post Details Extraction** - 🍪 **No Cookies Required** The scraper works without any LinkedIn login or cookies — simplifying setup and execution. ### ✨ You may also want to check out my other powerful actors: #### For people: - https://apify.com/freshdata/fresh-linkedin-profile-data - https://apify.com/freshdata/linkedin-open-profile-status - https://apify.com/freshdata/linkedin-open-to-work-status - https://apify.com/freshdata/linkedin-detect-activity-time #### For Sales Navigator searches: - https://apify.com/freshdata/linkedin-sales-navigator-scraper - https://apify.com/freshdata/linkedin-sales-account-scraper #### For companies: - https://apify.com/freshdata/linkedin-company-scraper - https://apify.com/freshdata/linkedin-company-insights-scraper - https://apify.com/freshdata/linkedin-company-by-domain - https://apify.com/freshdata/linkedin-company-custom-headcount #### For jobs: - https://apify.com/freshdata/linkedin-job-details-scraper - https://apify.com/freshdata/linkedin-job-scraper #### For posts: - https://apify.com/freshdata/linkedin-post-scraper - https://apify.com/freshdata/get-post-details - https://apify.com/freshdata/linkedin-company-post-scraper - https://apify.com/freshdata/linkedin-post-comments-scraper - https://apify.com/freshdata/reaction-scraper ### 🛠️ How It Works 1. 🔗 **Input** Provide an URN 2. ▶️ **Run the Scraper** Start the actor to extract rich profile post data in real time — results will be available in Apify's Dataset tab. ### 💰 Pricing 1. Paid users: $0.008/1 request = 1 "processing" events / 1 request ($8/1000 requests). 2. Free users: $0.8/1 request = 100 "processing" events/ 1 request ($800/1000 requests). ### 📥 Input Example ```json { "urn": "7267273010393358336" } ```` ### 📤 Output Example ```json { "data": { "images": [], "num_appreciations": 47, "num_comments": 310, "num_empathy": 405, "num_entertainments": 3, "num_interests": 26, "num_likes": 6813, "num_praises": 357, "num_reactions": 7651, "num_reposts": 97, "post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7315779816467656705/", "posted": "2025-04-09 16:57:08", "poster": { "first": "Bill", "headline": "Chair, Gates Foundation and Founder, Breakthrough Energy", "last": "Gates", "public_id": "williamhgates", "urn": "ACoAAA8BYqEBCGLg_vT_ca6mMEqkpp9nVffJ3hc" }, "poster_linkedin_url": "https://www.linkedin.com/in/williamhgates", "reshared": false, "shareUrl": "https://www.linkedin.com/posts/williamhgates_i-cant-celebrate-our-50th-anniversary-without-activity-7315779816467656705-FVNt?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAFIu57oBnNdFncOWMPPDIHUfZAMoqRc3dMs", "shareUrn": "7315779815297421316", "text": "I can’t celebrate our 50th anniversary without mentioning Kay Nishi, whose partnership and friendship were critical to Microsoft’s expansion internationally—in Japan and beyond. Not only is he an amazing thinker (and one of the most under-appreciated leaders in the company’s history), he’s also more like me than anybody I’ve ever met.", "time": "8 hours ago • Visible to anyone on or off LinkedIn", "urn": "7315779816467656705" }, "message": "ok" } ``` # Actor input Schema ## `urn` (type: `string`): The URN identifier for the query. ## Actor input object example ```json { "urn": "7267273010393358336" } ``` # 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 = { "urn": "7267273010393358336" }; // Run the Actor and wait for it to finish const run = await client.actor("freshdata/get-post-details").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 = { "urn": "7267273010393358336" } # Run the Actor and wait for it to finish run = client.actor("freshdata/get-post-details").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 '{ "urn": "7267273010393358336" }' | apify call freshdata/get-post-details --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=freshdata/get-post-details", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Get Post Details", "description": "The **Get Post Details** is a powerful tool designed to extract detailed reactions data from any profile posts — without the need for cookies or login.", "version": "0.0", "x-build-id": "9dwwrYXkdmaNp0mc5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/freshdata~get-post-details/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-freshdata-get-post-details", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/freshdata~get-post-details/runs": { "post": { "operationId": "runs-sync-freshdata-get-post-details", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/freshdata~get-post-details/run-sync": { "post": { "operationId": "run-sync-freshdata-get-post-details", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urn" ], "properties": { "urn": { "title": "URN", "type": "string", "description": "The URN identifier for the query." } } }, "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 } } } } } } } } } } ```