# LinkedIn Public Profile Scraper (`seeb/linkedin-public-profile-scraper`) Actor
Scrape simple public LinkedIn profile fields from provided URLs where accessible: name, headline, location, company clues, and source URL.
- **URL**: https://apify.com/seeb/linkedin-public-profile-scraper.md
- **Developed by:** [Techionik](https://apify.com/seeb) (community)
- **Categories:** Lead generation, Jobs, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.00 / 1,000 public profile rows
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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 Public Profile Scraper
Scrape simple public LinkedIn profile fields from provided URLs where accessible: name, headline, location, company clues, and source URL.
This actor is built for fast public-data runs with strict result caps, request timeouts, guarded error handling, and useful paid-result rows.
### What You Get
- structured source-backed rows
- signal or opportunity scoring where enough public data is available
- source issue notices in the key-value store when a page is blocked, login-only, unavailable, or empty
- optional change-detection rows for scheduled runs
- clean exports through Apify datasets, API, CSV, Excel, JSON, and integrations
### Profit And Cost Control
- Use low result caps for tests.
- The actor stops before the configured runtime guard.
- Failed public pages are recorded as run notices instead of crashing the run or creating paid dataset rows.
- Pricing should be set per delivered useful row, not per raw page attempt.
### Notes
- Works only with public pages and public APIs available during the run.
- Some platforms may limit public access or return less data without login.
# Actor input Schema
## `urls` (type: `array`):
Public LinkedIn profile URLs, public profile pages, job URLs, company career URLs, or search result pages.
## `intentKeywords` (type: `array`):
Optional keywords to score hiring or profile intent.
## `maxResults` (type: `integer`):
Maximum dataset rows to write. Keep low for tests to control cloud cost.
## `monitorChanges` (type: `boolean`):
Save a snapshot and compare future runs.
## `onlyChanges` (type: `boolean`):
When change detection is enabled, output only new or changed rows.
## `maxRunSeconds` (type: `integer`):
Hard runtime guard to avoid timeout and spend surprises.
## `requestTimeoutSeconds` (type: `integer`):
Timeout per public HTTP request.
## Actor input object example
```json
{
"urls": [
{
"url": "https://www.linkedin.com/in/satyanadella/"
}
],
"intentKeywords": [
"salesforce",
"ai engineer",
"revops",
"growth marketer",
"crm"
],
"maxResults": 25,
"monitorChanges": false,
"onlyChanges": false,
"maxRunSeconds": 180,
"requestTimeoutSeconds": 15
}
````
# Actor output Schema
## `results` (type: `string`):
Open the default dataset to view structured rows, source URLs, scores, and scraped timestamps.
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {};
// Run the Actor and wait for it to finish
const run = await client.actor("seeb/linkedin-public-profile-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {}
# Run the Actor and wait for it to finish
run = client.actor("seeb/linkedin-public-profile-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 seeb/linkedin-public-profile-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=seeb/linkedin-public-profile-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Public Profile Scraper",
"description": "Scrape simple public LinkedIn profile fields from provided URLs where accessible: name, headline, location, company clues, and source URL.",
"version": "0.1",
"x-build-id": "BAiJ7QeADrge4xYe5"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/seeb~linkedin-public-profile-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-seeb-linkedin-public-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/seeb~linkedin-public-profile-scraper/runs": {
"post": {
"operationId": "runs-sync-seeb-linkedin-public-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/seeb~linkedin-public-profile-scraper/run-sync": {
"post": {
"operationId": "run-sync-seeb-linkedin-public-profile-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"urls"
],
"properties": {
"urls": {
"title": "Source URLs",
"type": "array",
"description": "Public LinkedIn profile URLs, public profile pages, job URLs, company career URLs, or search result pages.",
"default": [
{
"url": "https://www.linkedin.com/in/satyanadella/"
}
],
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"intentKeywords": {
"title": "Intent Keywords",
"type": "array",
"description": "Optional keywords to score hiring or profile intent.",
"default": [
"salesforce",
"ai engineer",
"revops",
"growth marketer",
"crm"
],
"items": {
"type": "string"
}
},
"maxResults": {
"title": "Max Results",
"minimum": 1,
"maximum": 1000,
"type": "integer",
"description": "Maximum dataset rows to write. Keep low for tests to control cloud cost.",
"default": 25
},
"monitorChanges": {
"title": "Detect Changes",
"type": "boolean",
"description": "Save a snapshot and compare future runs.",
"default": false
},
"onlyChanges": {
"title": "Output Only Changes",
"type": "boolean",
"description": "When change detection is enabled, output only new or changed rows.",
"default": false
},
"maxRunSeconds": {
"title": "Max Run Seconds",
"minimum": 30,
"maximum": 900,
"type": "integer",
"description": "Hard runtime guard to avoid timeout and spend surprises.",
"default": 180
},
"requestTimeoutSeconds": {
"title": "Request Timeout Seconds",
"minimum": 5,
"maximum": 30,
"type": "integer",
"description": "Timeout per public HTTP request.",
"default": 15
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```