# LinkedIn Post Comments Scraper & Engaged Leads (`chirpy_polygon/linkedin-post-comments-lead-scraper`) Actor

Extract LinkedIn post comments and commenter details in bulk, including text, author name, headline, profile URL, date, likes, replies, and clean lead-ready output.

- **URL**: https://apify.com/chirpy\_polygon/linkedin-post-comments-lead-scraper.md
- **Developed by:** [Bhojraj Pilaniya](https://apify.com/chirpy_polygon) (community)
- **Categories:** Lead generation, Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.60 / 1,000 post comments

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?

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 Post Comments Scraper & Engaged Leads

Extract clean, deduplicated, CSV-ready linkedin post comments without supplying LinkedIn or Instagram cookies. This Actor validates inputs, runs maintained source collection, normalizes changing source fields into a stable schema, removes duplicate records, and preserves the raw result for advanced users.

### Best use cases

- engaged lead discovery
- social selling research
- comment sentiment research
- event prospecting
- influencer audience analysis

### What you get

- `commentText`
- `authorName`
- `authorHeadline`
- `authorUrl`
- `postedAt`
- `reactionCount`
- `likeCount`
- `isReply`
- `postUrl`
- `commentUrl`
- `sourceActorRunId` for troubleshooting and traceability
- `raw` containing the complete source item when you need extra fields

### Example input

```json
{
  "postUrls": [
    "https://www.linkedin.com/posts/example/"
  ],
  "maxCommentsPerPost": 25,
  "includeReplies": false
}
```

### Example output

```json
{
  "commentText": "This is a useful update.",
  "authorName": "Example Person",
  "authorHeadline": "VP Sales at Example",
  "authorUrl": "https://www.linkedin.com/in/example/",
  "postedAt": "2026-08-20T12:00:00Z",
  "likeCount": 8,
  "isReply": false
}
```

### How it works

1. Enter one or more URLs, names, or usernames in the input form.
2. The Actor validates and deduplicates your input.
3. A maintained no-cookie source Actor collects the live public data.
4. Results are normalized into consistent fields and duplicate records are removed.
5. Download the dataset as JSON, CSV, Excel, XML, or RSS, or connect it to your workflow through the Apify API.

### Pricing and cost control

This Actor uses pay-per-result pricing. You are charged for unique records saved to this Actor's dataset. Store discounts are applied automatically by Apify for higher subscription tiers.

The advanced source cost limit is automatically calculated from your requested item limits. Set `sourceMaxTotalChargeUsd` only when you need a stricter custom cap. A source run can still return zero records when a URL is invalid, private, removed, or has no matching public content.

### Reliability notes

- No LinkedIn or Instagram cookie is requested from you.
- Duplicate inputs and duplicate result records are removed.
- Invalid URLs fail early with a clear message.
- The raw source item is retained so downstream integrations do not lose uncommon fields.
- Public platform pages and schemas can change. Failed source runs are surfaced with their run ID for debugging.

### Responsible use

Only collect publicly available data that you are legally permitted to process. Follow applicable privacy, data protection, anti-spam, copyright, and platform rules. Do not use this Actor for harassment, unlawful profiling, credential collection, or abusive automation.

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn, Instagram, Meta, or Microsoft. Product names and trademarks belong to their respective owners.

# Actor input Schema

## `dryRun` (type: `boolean`):

Validate the Actor with a free sample output without requesting live source data.

## `postUrls` (type: `array`):

One LinkedIn post or feed update URL per row.

## `maxCommentsPerPost` (type: `integer`):

Maximum comments returned for each post URL.

## `postedLimit` (type: `string`):

Only return comments newer than this relative period.

## `includeReplies` (type: `boolean`):

Also collect replies beneath top-level comments.

## `sourceMaxTotalChargeUsd` (type: `number`):

Advanced safety cap for the underlying data collection run. Leave empty for an automatic cap based on your requested result limit.

## `sourceWaitSecs` (type: `integer`):

Maximum time to wait for the underlying data collection run.

## Actor input object example

```json
{
  "dryRun": false,
  "postUrls": [
    "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7/"
  ],
  "maxCommentsPerPost": 25,
  "postedLimit": "any",
  "includeReplies": false,
  "sourceWaitSecs": 1800
}
```

# 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 = {
    "postUrls": [
        "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("chirpy_polygon/linkedin-post-comments-lead-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 = { "postUrls": ["https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7/"] }

# Run the Actor and wait for it to finish
run = client.actor("chirpy_polygon/linkedin-post-comments-lead-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 '{
  "postUrls": [
    "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7/"
  ]
}' |
apify call chirpy_polygon/linkedin-post-comments-lead-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,chirpy_polygon/linkedin-post-comments-lead-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/cCkwBer8gsVw8R23z/builds/yyfPXxL5ceGN5UAGr/openapi.json