# LinkedIn Company Posts Scraper (No Cookies) (`baseball/linkedin-company-posts-scraper`) Actor

Extract posts from LinkedIn companies including content, media, engagement, reactions, comments and more. No cookies or account required. Concurrency + fast response times make mass scraping fast ⚡

- **URL**: https://apify.com/baseball/linkedin-company-posts-scraper.md
- **Developed by:** [Baseball](https://apify.com/baseball) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 linkedin-company-posts

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🏢 LinkedIn Company Post Scraper

Extract LinkedIn posts published by a company page using its LinkedIn company URL.

This actor is designed for **company content monitoring**, **competitive research**, **social media analysis**, **engagement tracking**, **sales intelligence**, **content research**, and **automated workflows**.

Simply provide a LinkedIn company URL, configure the number of posts and date filters, and receive structured post data in your Apify dataset.

***

### ⚙️ Key Features

- **Company-specific scraping** — scrape posts published by a LinkedIn company page
- **LinkedIn company URL input** — provide the full LinkedIn company URL
- **Post limit** — control the maximum number of posts to collect
- **Date filtering** — collect posts published after a specific date
- **Repost control** — choose whether reposted/shared content should be included
- **Structured post data** — receive post content, URLs, timestamps, engagement metrics, author information, and media data where available
- **File naming** — specify a custom output file name

***

### 📥 Input

The actor accepts JSON input.

#### Example

```json
{
  "company": "https://www.linkedin.com/company/google",
  "fileName": "my-company-posts",
  "includeReposts": false,
  "maxPosts": 50,
  "postsAfterDate": "2026-08-01",
  "orderId": ""
}
```

#### 🧩 Input Parameters

| Parameter | Type | Required | Description |
|---|---|---|---|
| `company` | String | ✅ Yes | Full LinkedIn company page URL |
| `fileName` | String | No | Custom name for the output file |
| `includeReposts` | Boolean | No | Whether reposted/shared posts should be included |
| `maxPosts` | Integer | No | Maximum number of posts to scrape |
| `postsAfterDate` | String | No | Only collect posts published after this date |
| `orderId` | String | No | Optional external order, customer, or workflow reference ID |

***

### 📊 Data You'll Receive

The scraper returns structured LinkedIn post data. The exact fields can vary depending on the post and the information available from LinkedIn.

#### 📝 Post Information

Typical post information includes:

- Post ID
- LinkedIn post URL
- Post content/text
- Post type
- Publication timestamp
- Publication date
- Relative posting time (where available)

#### 🏢 Company / Author Information

Depending on the post, the dataset may include:

- Company name
- Company LinkedIn URL
- Author name
- Author LinkedIn URL
- Public identifier
- Author type
- Author information
- Author profile image/avatar (where available)

> Company-post data can include either company or author information depending on how the LinkedIn post is represented.

#### 📈 Engagement Metrics

Where available, engagement information may include:

- Likes
- Comments
- Shares
- Total reactions
- Reaction counts
- Reaction type breakdowns

**Example:**

```json
"engagement": {
  "likes": 2916,
  "comments": 328,
  "shares": 153,
  "reactions": [
    {
      "type": "LIKE",
      "count": 2477
    }
  ]
}
```

#### 🖼️ Media & Content

Depending on the post, the scraper may return:

- Post images and image URLs
- Videos and video URLs
- External links
- Documents (title, page count, URL)
- Reposted/shared content (when enabled)

> These fields are returned when the corresponding media or content is available on the post.

***

### 📄 Sample Output

A typical result looks like this:

```json
{
  "type": "post",
  "id": "7329207003942125568",
  "linkedinUrl": "https://www.linkedin.com/posts/example-company_example-post-activity-7329207003942125568",
  "content": "Example LinkedIn company post content...",
  "author": {
    "publicIdentifier": "example-company",
    "type": "company",
    "name": "Example Company",
    "linkedinUrl": "https://www.linkedin.com/company/example-company"
  },
  "postedAt": {
    "timestamp": 1747419119821,
    "date": "2025-05-16T18:11:59.821Z",
    "postedAgoShort": "6d",
    "postedAgoText": "6 days ago"
  },
  "postImages": [],
  "engagement": {
    "likes": 2916,
    "comments": 328,
    "shares": 153,
    "reactions": [
      {
        "type": "LIKE",
        "count": 2477
      }
    ]
  }
}
```

> **Note:** The exact output fields may vary depending on the individual LinkedIn post and the data available for that post.

***

### 🚀 How to Use

#### Step 1 — Create an Apify account

Create or log in to your [Apify account](https://apify.com).

#### Step 2 — Open the actor

Open the **LinkedIn Company Post Scraper** actor.

#### Step 3 — Enter the company URL

Provide the LinkedIn company page you want to scrape.

```
https://www.linkedin.com/company/google
```

#### Step 4 — Configure scraping options

Optionally configure:

- Maximum number of posts
- Publication date filter
- Repost inclusion
- Output file name
- External order ID

#### Step 5 — Run the actor

Start the actor and wait for the scraping process to complete.

#### Step 6 — Export the results

Download or process the resulting dataset using formats such as:

- **JSON**
- **CSV**
- **Excel**

The data can also be connected to databases, CRMs, spreadsheets, analytics tools, and automated workflows.

***

### 📦 Complete Input Example

```json
{
  "company": "https://www.linkedin.com/company/google",
  "fileName": "my-company-posts",
  "includeReposts": false,
  "maxPosts": 50,
  "postsAfterDate": "2026-08-01",
  "orderId": ""
}
```

This configuration:

- Scrapes the LinkedIn company page
- Collects up to **50 posts**
- Collects posts after **August 1, 2026**
- Excludes reposts
- Uses `my-company-posts` as the output file name
- Does not specify an external order ID

***

### ⚠️ Important Notes

- `company` should contain a valid LinkedIn company page URL
- `maxPosts` controls the maximum number of posts returned
- `postsAfterDate` filters posts based on publication date
- `includeReposts` controls whether reposted/shared content is included
- `fileName` can be used to specify a custom output file name
- `orderId` is optional and can be used to associate a run with an external workflow
- The actor may return **fewer posts than `maxPosts`** when fewer matching posts are available
- Output fields can vary depending on the individual LinkedIn post
- Not every post contains images, videos, documents, reactions, or comments
- Engagement and media fields are returned when the corresponding data is available
- Reposted/shared content is controlled by `includeReposts`
- Do not assume every post will contain every possible field

***

### 🎯 Summary

**LinkedIn Company Post Scraper** makes it easy to collect structured LinkedIn posts from a company page.

Simply provide a LinkedIn company URL, configure the number of posts and date filter, choose whether to include reposts, and run the actor.

The resulting data can be used for:

- Competitive intelligence
- Content research
- Social media monitoring
- Engagement analysis
- Sales intelligence
- Account research
- Automated data pipelines

# Actor input Schema

## `company` (type: `string`):

LinkedIn company URL (https://www.linkedin.com/company/google), username/slug (google), or company name (Google LLC).

## `fileName` (type: `string`):

Tag name for this run. Used to identify your output file. Example: google-posts-june

## `maxPosts` (type: `integer`):

Maximum number of posts to scrape. Set to 0 for unlimited.

## `postsAfterDate` (type: `string`):

Only scrape posts published after this date. Format: YYYY-MM-DD.

## `includeReposts` (type: `boolean`):

Set to true to include reposts in results. Set to false for original posts only.

## `orderId` (type: `string`):

Optional order ID to tag this run. Useful for tracking requests.

## Actor input object example

```json
{
  "company": "https://www.linkedin.com/company/google",
  "fileName": "my-company-posts",
  "maxPosts": 50,
  "postsAfterDate": "2026-08-01",
  "includeReposts": false,
  "orderId": ""
}
```

# Actor output Schema

## `results` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "company": "https://www.linkedin.com/company/google",
    "fileName": "my-company-posts",
    "postsAfterDate": "2026-08-01"
};

// Run the Actor and wait for it to finish
const run = await client.actor("baseball/linkedin-company-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "company": "https://www.linkedin.com/company/google",
    "fileName": "my-company-posts",
    "postsAfterDate": "2026-08-01",
}

# Run the Actor and wait for it to finish
run = client.actor("baseball/linkedin-company-posts-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "company": "https://www.linkedin.com/company/google",
  "fileName": "my-company-posts",
  "postsAfterDate": "2026-08-01"
}' |
apify call baseball/linkedin-company-posts-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,baseball/linkedin-company-posts-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/rZQ3gKDbaappADayq/builds/fHZQ8AaKi8JcwtzSX/openapi.json