LinkedIn Posts Scraper

What is LinkedIn Posts Scraper?

LinkedIn Posts Scraper collects public LinkedIn posts from keyword searches, public company feeds, and exact post URLs. It is designed for readers who need one record per post, with fields such as post text, author details, engagement counts, media URLs, comments preview, provider provenance, and scrape metadata. The result is a dataset of structured public post records plus a machine-readable run summary in key-value store output.

This Actor is available through Apify and usable through Apify MCP. It accepts public LinkedIn source inputs and returns one dataset row per scraped post, which makes each record a single post-level observation from the chosen source. Typical output fields include postUrl, postId, publishedAt, text, authorName, authorUrl, companyName, reactionCount, commentCount, shareCount, engagementCount, mediaUrl, and provider.

Best fit and connected workflows

This Actor fits workflows that start from public LinkedIn discovery and end with structured records for analysis or downstream automation. It routes naturally into:

• keyword-based social listening for public post discovery
• company page monitoring for recent public company posts
• exact URL enrichment for a known public LinkedIn post, feed update, or article
• agent pipelines that need a compact post record with provenance
• B2B research and lead qualification flows built on public post activity

If your workflow begins with a search phrase, a company page URL, or a post URL, this Actor turns that input into consistent post rows that can be filtered, reviewed, or passed to another step.

Practical scenario

A sales analyst wants to review public posts about "AI agents" from the last month. She enters one search query, sets a post cap, and enables enrichment for fuller post detail. The returned rows include authorName, postUrl, text, reactionCount, commentCount, shareCount, and provider. She uses those fields to shortlist posts for manual review, then opens the source post URLs to assess messaging trends and outreach relevance.

Input

Provide at least one source: search query, company URL, or exact post URL.

Field	Type	Purpose
searchQueries	array of strings	Keywords or phrases to search in public LinkedIn posts.
companyUrls	array of strings	Public LinkedIn company page URLs whose recent posts should be scraped.
postUrls	array of strings	Exact public LinkedIn post, feed update, or article URLs to fetch.
maxPosts	integer	Maximum number of post records to save across all sources.
datePosted	string	Freshness window for keyword search (last hour, day, week, month, year).
postedAfter	string	Keep only posts published on or after this date (for example 2026-11-01). Older posts are dropped and not billed.
maxAgeDays	integer	Keep only posts from the last N days. Older posts are dropped and not billed.
minReactions	integer	Keep only posts with at least this many reactions. Others are dropped and not billed.
minComments	integer	Keep only posts with at least this many comments. Others are dropped and not billed.
maxSearchPages	integer	Maximum search pages for keyword pagination.
maxPagesPerCompany	integer	Maximum pages to fetch per company URL.
startCursor	string	Cursor for continuing a keyword search run.
providerOrder	string	Provider order for company feeds and post-detail enrichment.
enrichPostDetails	boolean	Off by default. Fetch each post's full detail with one extra lookup; those rows use the full-detail price.
includeComments	boolean	Include up to five public comments from post detail payloads.
outputMode	string	full or compact output shape.
includeRawData	boolean	Attach raw provider payloads to each dataset item.

Focused JSON example:

{
  "searchQueries": ["ai agents", "sales automation"],
  "datePosted": "last-month",
  "maxPosts": 25,
  "maxSearchPages": 3,
  "enrichPostDetails": true,
  "includeComments": false,
  "outputMode": "compact"
}

Output

Each dataset item represents one public LinkedIn post row.

Field	Type	Purpose
sourceType	string	Discovery method: search, company, or postUrl.
sourceInput	string	Search query, company URL, or exact post URL that produced the row.
postUrl	string or null	Public LinkedIn URL for the post, feed update, or article.
postId	string or null	LinkedIn activity, share, article, or provider identifier.
publishedAt	string or null	Provider-returned publication date or timestamp.
text	string or null	Visible post body, article text, or provider description.
authorName	string or null	Public name of the post author.
authorUrl	string or null	Public LinkedIn profile or page URL for the author.
companyName	string or null	Company name for company-sourced or enriched rows.
reactionCount	integer or null	Total reaction count when available.
commentCount	integer or null	Public comment count when available.
shareCount	integer or null	Share or repost count when available.
engagementCount	integer or null	Convenience total of available engagement counts.
mediaUrl	string or null	Primary media or image URL when available.
hashtags	array	Hashtags found in the post text (without the # sign).
links	array	Web links found in the post text (full output mode).
provider	string	Managed provider or provider chain used for the row.
scrapedAt	string	ISO timestamp when the Actor saved the row.

Illustrative JSON record:

{
  "sourceType": "search",
  "sourceInput": "ai agents",
  "postUrl": "https://www.linkedin.com/posts/example_activity-7354600338621906944",
  "postId": "7354600338621906944",
  "publishedAt": "2025-01-12T10:15:00Z",
  "text": "Public post text",
  "authorName": "Example Author",
  "authorUrl": "https://www.linkedin.com/in/example-author/",
  "companyName": "Example Company",
  "reactionCount": 42,
  "commentCount": 5,
  "shareCount": 3,
  "engagementCount": 50,
  "mediaUrl": "https://example.com/image.jpg",
  "scrapedAt": "2025-01-12T10:16:02Z"
}

The default output also includes a machine-readable run summary in the key-value store, with counters such as records saved, provider attempts, retries, status codes, billing counters, dedupe counts, stop reason, and provider usage.

How it works

This Actor uses managed provider-backed collection for public LinkedIn posts. Search mode uses Google-indexed public LinkedIn results through the primary data provider. Company feeds and exact post URLs are handled through the configured provider order, with the default provider order as the default. When post enrichment is enabled, the Actor can fetch fuller text, engagement counts, media, and comments preview when the provider exposes them. Raw provider payloads are available only when includeRawData is enabled.

Pricing

Pay per event. Platform usage (compute and storage) is included in the price. You pay only for posts that are saved: posts removed by your date, reactions or comments filters are not billed.

New prices start on 2026-11-25. Until then every saved post costs the current $0.006.

What you get	Price from 2026-11-25	Event
Post from a keyword search or company feed	$0.004 per post	post-scraped
Post fetched by exact URL, or any post when enrichPostDetails is on	$0.013 per post	post-detail-scraped
Actor start	$0.00005	one per run

Example run (from 2026-11-25)	Posts	Cost
Keyword search, 10 posts	10	about $0.04
Keyword search, 100 posts	100	about $0.40
Three exact post URLs	3	about $0.039

Paid Apify plans get plan discounts: Silver 4% and Gold and above 9% off both events. Set maxPosts to cap spend for any run or agent call.

Free Apify plan

Runs started from a free Apify plan return up to 25 results per run, with every input mode and output field available. Paid Apify plans have no per-run limit, so your usual result settings apply.

Use with AI agents (MCP)

This Actor is available through Apify MCP as a tool for retrieving structured public LinkedIn post records. The exact Actor identity is khadinakbar/linkedin-posts-scraper.

Find recent public LinkedIn posts about AI agents, return the post text, author name, engagement counts, source URL, and provider for each row, and keep the result compact for downstream agent processing.

The output is suitable interpreted as post-level records. sourceType and sourceInput explain how each row was discovered, provider shows the managed provider or chain that supplied it, and scrapedAt marks when the Actor saved the row. postUrl and postId identify the public post, while counts such as reactionCount, commentCount, shareCount, and engagementCount support ranking or filtering.

For agent workflows, compact output keeps the record smaller, while full output includes richer post fields when available. includeComments adds up to five public comments inside the post-detail payload. Search mode uses provider pagination through maxSearchPages, and company mode uses maxPagesPerCompany. Billing follows the saved post count, so maxPosts is a practical cap for agent calls and test runs.

Example using the Apify API

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const run = await client.actor('khadinakbar/linkedin-posts-scraper').call({
  searchQueries: ['ai agents'],
  datePosted: 'last-month',
  maxPosts: 10,
  outputMode: 'compact',
});

const datasetId = run.defaultDatasetId;
const { items } = await client.dataset(datasetId).listItems();
console.log(items);

Set APIFY_TOKEN in your environment before running the script. The dataset readback returns the saved post rows from the default dataset.

Best results and outcome guidance

Use one source family at a time when the workflow starts with a narrow goal: keyword search for topic discovery, company URLs for page monitoring, and exact post URLs for single-post enrichment. Lower maxPosts for quick agent calls, then raise it when you want a broader sample. Search and company rows already include author, reactions and comments, so leave enrichPostDetails off unless you need the fuller text or comments preview. To find high-performing posts, set minReactions or minComments and maxAgeDays. If you are testing cursor behavior, adjust startCursor and maxSearchPages together for search runs.

Which Actor for which job

You have	Use	Why
A keyword or topic, many posts	this Actor	Search with date, reactions and comments filters
A company page	this Actor	Recent company posts in the same output shape
One known post URL, full record	LinkedIn Post Details Scraper	Built for single-URL lookups
A person's profile, all their posts	LinkedIn Profile Posts Scraper	Person feed
Who commented on or reacted to a post	LinkedIn Post Engagers Scraper	People, not posts

What's new

• 2026-11-10: new filters postedAfter, maxAgeDays, minReactions, minComments (filtered posts are not billed); new hashtags and links fields; full-detail lookups are now opt-in; runs stop early with a partial result instead of timing out.

Continue the workflow

• Then use LinkedIn Profile Comments Scraper — Engagement Leads to add Linkedin engagement evidence to records selected with LinkedIn Posts Scraper.
• Then use LinkedIn Profile Details Scraper — Profile by URL to extend LinkedIn Posts Scraper research with a complementary enrichment contract.

Design note

I found that the dataset contract marks sourceType, sourceInput, provider, and scrapedAt as required, which makes each record traceable even when many other fields are optional or provider-dependent.

FAQ

Can this Actor start from a keyword search and a company URL in the same run?

Yes. The input schema accepts searchQueries, companyUrls, and postUrls together, and the Actor combines the selected sources into one output set.

What does sourceType tell me?

It tells you how the post was discovered: search, company, or postUrl.

Which fields are useful for routing a post to downstream analysis?

postUrl, postId, authorName, companyName, publishedAt, reactionCount, commentCount, shareCount, and engagementCount are the most common routing fields.

When should I use compact output?

Use compact when you want a smaller record shape for MCP agents, tables, or simple pipelines.

When should I use full output?

Use full when you want richer post fields such as media lists, author images, and additional company context where the provider exposes them.

Am I charged for posts my filters remove?

No. Posts removed by postedAfter, maxAgeDays, minReactions or minComments are not saved and not billed.

Why are exact URLs priced higher?

An exact URL needs its own lookup for each post, while search results return ten posts per lookup.

How do I continue a keyword search?

Use startCursor with a previous the primary data provider search cursor and keep maxSearchPages aligned with the search depth you want.

Responsible use

This Actor is intended for public LinkedIn post data returned by managed provider APIs. Review LinkedIn's terms, applicable laws, and your own use case before running large-scale collection. Use the output for lawful analysis, monitoring, enrichment, and agent workflows that respect privacy and platform rules.