# Linkedin Post Scraper ✅ No cookies (`supreme_coder/linkedin-post`) Actor

Scrape unlimited Linkedin posts without risking your Linkedin account. Live data, Super fast scraping at affordable cost. High success rate

- **URL**: https://apify.com/supreme\_coder/linkedin-post.md
- **Developed by:** [Supreme Coder](https://apify.com/supreme_coder) (community)
- **Categories:** Social media, Lead generation, Automation
- **Stats:** 15,434 total users, 1,426 monthly users, 100.0% runs succeeded, 588 bookmarks
- **User rating**: 4.13 out of 5 stars

## Pricing

from $2.00 / 1,000 cost per post scrapeds

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 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

Scrape posts from linkedin without providing cookies or risking account ban
Scrape posts from linkedin in realtime and get latest data

This is the **hybrid** variant: every request is randomly routed to either the
API-proxy backend or the browser-proxy backend, according to configurable
weights. Both backends expose the same client interface, so `main.js` calls the
common methods without knowing which backend serves any given request.

It supports scraping posts from

- Linkedin users
- Companies
- Linkedin posts search

Configure the split with the `hybridWeights` input (or the `HYBRID_API_WEIGHT` /
`HYBRID_BROWSER_WEIGHT` env vars), e.g. `{ "api": 0.7, "browser": 0.3 }`.
Defaults to an even 50/50 split.

Use cases

- Generate hyper personalized cold emails based on user's posts
- Find posts related to your niche and generate leads

# Actor input Schema

## `urls` (type: `array`):

Supported URLs: Linkedin post search URL, Linkedin user or company profile URL, Linkedin post URL

## `limitPerSource` (type: `integer`):

Limit number of posts scraped per source URL, leave empty for unlimited

## `scrapeUntil` (type: `string`):

Use this field if you want to only scrape posts newer than given date

## `deepScrape` (type: `boolean`):

Get more information such as likes, comments etc

## `fetchDocumentDetails` (type: `boolean`):

Fetch attached document details from posts with transcripts and all available pages as images. If not enabled, only first 4 page images will be available

## `numComments` (type: `integer`):

Number of comments to fetch for each post

## `numLikes` (type: `integer`):

Number of liked users to fetch for each post

## `rawData` (type: `boolean`):

Push the scraped data directly to the dataset without any processing and filtering. This might be useful if you are looking for some missing data in the dataset

## Actor input object example

```json
{
  "urls": [
    "https://www.linkedin.com/posts/linkedin_no-is-a-complete-sentence-activity-7247998907798978560-J_hB?utm_source=share&utm_medium=member_desktop",
    "https://www.linkedin.com/company/amazon",
    "https://www.linkedin.com/search/results/content/?datePosted=%22past-24h%22&keywords=ai&origin=FACETED_SEARCH"
  ],
  "limitPerSource": 10,
  "deepScrape": true,
  "fetchDocumentDetails": false,
  "numComments": 10,
  "numLikes": 10,
  "rawData": false
}
```

# 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 = {
    "urls": [
        "https://www.linkedin.com/posts/linkedin_no-is-a-complete-sentence-activity-7247998907798978560-J_hB?utm_source=share&utm_medium=member_desktop",
        "https://www.linkedin.com/company/amazon",
        "https://www.linkedin.com/search/results/content/?datePosted=%22past-24h%22&keywords=ai&origin=FACETED_SEARCH"
    ],
    "limitPerSource": 10,
    "numComments": 10,
    "numLikes": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("supreme_coder/linkedin-post").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 = {
    "urls": [
        "https://www.linkedin.com/posts/linkedin_no-is-a-complete-sentence-activity-7247998907798978560-J_hB?utm_source=share&utm_medium=member_desktop",
        "https://www.linkedin.com/company/amazon",
        "https://www.linkedin.com/search/results/content/?datePosted=%22past-24h%22&keywords=ai&origin=FACETED_SEARCH",
    ],
    "limitPerSource": 10,
    "numComments": 10,
    "numLikes": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("supreme_coder/linkedin-post").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 '{
  "urls": [
    "https://www.linkedin.com/posts/linkedin_no-is-a-complete-sentence-activity-7247998907798978560-J_hB?utm_source=share&utm_medium=member_desktop",
    "https://www.linkedin.com/company/amazon",
    "https://www.linkedin.com/search/results/content/?datePosted=%22past-24h%22&keywords=ai&origin=FACETED_SEARCH"
  ],
  "limitPerSource": 10,
  "numComments": 10,
  "numLikes": 10
}' |
apify call supreme_coder/linkedin-post --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Wpp1BZ6yGWjySadk3/builds/3drr9u2Jado8vtF5M/openapi.json