# Profile Comments Scraper for LinkedIn \[No Cookies] (`apimaestro/linkedin-profile-comments`) Actor

Linkedin User comments scraper:
Extract comments LinkedIn profiles and users including post content, reactions, stats, media attachments and more.

- **URL**: https://apify.com/apimaestro/linkedin-profile-comments.md
- **Developed by:** [API Maestro](https://apify.com/apimaestro) (community)
- **Categories:** Lead generation, Social media
- **Features:** Limited permissions
- **Stats:** 1,898 total users, 185 monthly users, 100.0% runs succeeded, 53 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $5.00 / 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/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 Profile Comments Scraper

Extract public Comments made by Linkedin User. Get structured data including reaction and posts

#### For other LinkedIn actors, check: https://apify.com/apimaestro

### ✨ Key Features

- No account needed:  Don't risk your account security by sharing your cookies and don't get your account restricted or banned!
- Recent Comments
- Post content and media
- Reaction counts by type (likes, comments, etc.)
- Post URLs for sharing
- Media attachments (images, articles, etc.)
- Pagination support for older posts

### 🔧 Simple Usage

Provide a LinkedIn profile username to get their recent comments and activity. The username is the last part of a LinkedIn profile URL (e.g., 'satyanadella' from linkedin.com/in/satyanadella).

### Automatic Pagination

Simply set the total number of comments you want the actor to scrape per Profile on `Result Limit Per Profile` field.

### Output Preview

```json
{
    "comments": [
        {
            "posted_at": "2 months ago",
            "text": "Post content here...",
            "url": "https://www.linkedin.com/comments/...",
            "author": {
                "first_name": "Satya",
                "last_name": "Nadella",
                "headline": "Chairman and CEO at Microsoft",
                "profile_url": "https://www.linkedin.com/in/satyanadella",
                "profile_picture": "https://..."
            },
            "stats": {
                "total_reactions": 2508,
                "likes": 2048,
                "appreciations": 63,
                "empathy": 195,
                "interests": 20,
                "praises": 182,
                "comments": 159,
                "reposts": 159
            },
            "media": {
                "type": "article",
                "url": "https://...",
                "thumbnail": "https://..."
            }
        }
    ],
    "metadata": {
        "pagination_token": "dXJuOmxpOmFj..."
    }
}
```

<br>

***

**Disclaimer:** This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of LinkedIn Corporation. All trademarks are property of their respective owners.

# Actor input Schema

## `usernames` (type: `array`):

List of LinkedIn profile identifiers. You can use either:

- Usernames (e.g., 'satyanadella')
- Profile URLs (e.g., 'https://www.linkedin.com/in/satyanadella')
- Comma-separated values will be split automatically

## `limit` (type: `integer`):

Maximum number of comments to extract per profile (1-3000). The actor will automatically paginate through all pages until reaching this limit. Default is 100 comments per profile

## Actor input object example

```json
{
  "usernames": [
    "satyanadella",
    "https://www.linkedin.com/in/williamhgates/"
  ],
  "limit": 100
}
```

# 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 = {
    "usernames": [
        "satyanadella",
        "https://www.linkedin.com/in/williamhgates/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apimaestro/linkedin-profile-comments").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 = { "usernames": [
        "satyanadella",
        "https://www.linkedin.com/in/williamhgates/",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("apimaestro/linkedin-profile-comments").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 '{
  "usernames": [
    "satyanadella",
    "https://www.linkedin.com/in/williamhgates/"
  ]
}' |
apify call apimaestro/linkedin-profile-comments --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apimaestro/linkedin-profile-comments"
        }
    }
}
```

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/7TNcROe1C2CQDO3wl/builds/g8FihS8avApmzmgK4/openapi.json