# LinkedIn Company Feed & Competitor Content Tracker (`monumental_world/linkedin-company-feed-scraper`) Actor

Scrape the complete post history from any LinkedIn company page. Returns structured data on every post — content, engagement metrics, reaction breakdown, and media. Designed for competitive intelligence, brand research, and content analysis.

- **URL**: https://apify.com/monumental\_world/linkedin-company-feed-scraper.md
- **Developed by:** [Raised Pro](https://apify.com/monumental_world) (community)
- **Categories:** Social media, Lead generation
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 results

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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Company Feed & Competitor Content Tracker

Extract structured post-level data from any LinkedIn company page. Retrieve a company's complete content history with engagement metrics, reaction type distributions, media, and post classification — organized for analysis, dataset construction, and competitive intelligence workflows.

### Dataset Schema

| Field | Type | Description |
|---|---|---|
| `company_name` | string | Company page name |
| `company_linkedin_url` | string | Source company URL |
| `post_url` | string | Direct post link |
| `post_text` | string | Full post body |
| `post_type` | string | standard / article / document |
| `created_at` | ISO 8601 | Publication timestamp |
| `is_repost` | boolean | Reshared content flag |
| `num_likes` | integer | Total reactions |
| `num_comments` | integer | Comment count |
| `num_shares` | integer | Share count |
| `reaction_counts` | object | Per-type reaction breakdown |
| `media_attachments` | array | Attached media metadata |
| `author_name` | string | Publisher (company or individual) |
| `author_type` | string | company / person |
| `urn` | string | LinkedIn URN identifier |

### Research and Analysis Applications

**Competitive intelligence:** Compare content volume, posting frequency, and engagement rates across competitor company pages in a single dataset.

**Content strategy analysis:** Identify which post formats (text-only, documents, articles) generate highest engagement for a given industry.

**Brand communication research:** Study how companies respond to market events, product launches, or crises in their LinkedIn content.

**NLP dataset construction:** Build labeled corpora of corporate LinkedIn content for sentiment analysis or topic modeling.

### Input Parameters

```json
{
  "company_urls": [
    "https://www.linkedin.com/company/salesforce/",
    "https://www.linkedin.com/company/hubspot/"
  ],
  "post_type": "all",
  "max_posts": 200
}
```

### Pricing

$15 per 1,000 posts extracted. No subscription or minimum commitment.

### FAQ

**What is the maximum retrievable post history?**
LinkedIn limits access to approximately 200–500 posts per company page depending on posting volume. The actor retrieves all available posts up to the `max_posts` limit you set.

**Is the data timestamped?**
Yes. `created_at` is returned as an ISO 8601 timestamp for all posts, enabling time-series analysis.

**Can results be exported to a spreadsheet?**
Yes. Download directly from the Apify dataset as CSV, or use the API to pull JSON into your data warehouse.

# Actor input Schema

## `linkedin_url` (type: `string`):

The LinkedIn Company Url to scraping

## `maxPages` (type: `integer`):

Maximum number of pages to fetch (pagination handled automatically)

## Actor input object example

```json
{
  "linkedin_url": "https://www.linkedin.com/company/google/",
  "maxPages": 1
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("monumental_world/linkedin-company-feed-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("monumental_world/linkedin-company-feed-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 '{}' |
apify call monumental_world/linkedin-company-feed-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=monumental_world/linkedin-company-feed-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/fJTwsXLD7RT6Q04ES/builds/6HUM7n3BogdzvptEF/openapi.json