# LinkedIn Profile Scraper (`scrapemint/linkedin-profile-scraper`) Actor
Pull structured profile facts from any public LinkedIn member URL without a cookie or login. Each row carries name, headline, location, current company, current title, profile summary, top experience, top education, top skills, and profile photo. JSON. Pay per profile.
- **URL**: https://apify.com/scrapemint/linkedin-profile-scraper.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Lead generation, Social media, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per usage
This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Profile Scraper (No Login Required)
Pull structured profile facts from any public LinkedIn member URL. No cookies. No login. No Sales Navigator seat. Each row ships the member name, headline, location, current company, current title, public summary, top experience, top education, top skills, and profile photo. Pay per profile.
**Built for** B2B sales teams, recruiters, agencies, founders, and CRM enrichment pipelines that need clean structured contact records for prospecting, account research, and lead scoring.
**Keywords this actor ranks for:** linkedin profile scraper, linkedin people scraper, linkedin scraper no cookie, linkedin profile api, scrape linkedin profile without login, linkedin contact enrichment, linkedin lead scraper, linkedin headline scraper, linkedin experience scraper, linkedin education scraper, linkedin skills scraper, linkedin no login.
---
### Why this actor
| Other LinkedIn profile scrapers | **This actor** |
|---|---|
| Need your session cookie | Zero cookies, zero login |
| Risk your account on every run | Touches only public profile pages |
| Single big text blob | Name, headline, location, current title, current company, summary all parsed into discrete fields |
| Experience and education skipped | Top experience and education entries shipped per row |
| No skills surfaced | Top public skills shipped as an array |
---
### How it works
```mermaid
flowchart LR
A[Profile URL] --> B[Public profile page
no auth needed]
B --> C[Parse JSON-LD
top card and section blocks]
C --> D[Normalize into discrete fields]
D --> E[Push one row per profile]
E --> F[(JSON CSV Excel API)]
````
The actor hits the public `linkedin.com/in/{slug}` page through a residential proxy and pulls JSON-LD plus Open Graph meta plus DOM selectors. No cookie passes through the actor at any stage.
***
### What you get per row
```mermaid
flowchart LR
R[Profile row] --> R1[Identity
slug url name photo]
R --> R2[Pitch
headline summary location]
R --> R3[Current role
currentTitle currentCompany]
R --> R4[Career
experience education]
R --> R5[Skill graph
skills]
R --> R6[Reach
followerCount connectionCount]
```
Pipe straight into a CRM, an account scoring model, or an SDR sequencing tool.
***
### Quick start
**Enrich a list of contacts**
```json
{
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08"
]
}
```
**Sales prospecting (skip skills to keep rows lean)**
```json
{
"profileUrls": ["https://www.linkedin.com/in/williamhgates"],
"includeExperience": true,
"includeEducation": true,
"includeSkills": false
}
```
**Recruiter sourcing (full career graph)**
```json
{
"profileUrls": [
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/sundarpichai"
],
"includeExperience": true,
"includeEducation": true,
"includeSkills": true
}
```
***
### Sample output
```json
{
"slug": "satyanadella",
"url": "https://www.linkedin.com/in/satyanadella",
"name": "Satya Nadella",
"headline": "Chairman and CEO at Microsoft",
"location": "Redmond, Washington, United States",
"currentTitle": "Chairman and CEO",
"currentCompany": "Microsoft",
"summary": "As chairman and CEO of Microsoft, I define my mission...",
"photoUrl": "https://media.licdn.com/dms/image/...",
"followerCount": 11000000,
"connectionCount": 500,
"experience": [
{
"title": "Chairman and CEO",
"company": "Microsoft",
"dateRange": "Feb 2014 - Present",
"location": "Greater Seattle Area",
"description": null
}
],
"education": [
{
"school": "The University of Chicago Booth School of Business",
"degree": "MBA",
"field": null,
"dateRange": null
}
],
"skills": ["Cloud Computing", "Enterprise Software", "Leadership"],
"scrapedAt": "2026-05-08T10:00:00.000Z"
}
```
***
### Who uses this
| Role | Use case |
|---|---|
| B2B sales | Enrich a target prospect list with title, company, location before outreach |
| RevOps | Backfill missing contact-level fields in a CRM without paying a data vendor seat |
| Recruiter | Score candidates by experience and education before reaching out |
| Founder | Research target hires and advisors before booking a call |
| Investor | Pull founder and exec backgrounds for diligence packets |
| ABM lead | Cluster contacts by current title and seniority for tiered plays |
***
### Input reference
| Field | Type | What it does |
|---|---|---|
| `profileUrls` | string\[] | LinkedIn member URLs or bare slugs. Required. |
| `includeExperience` | boolean | Keep the experience array on each row. Default true. |
| `includeEducation` | boolean | Keep the education array on each row. Default true. |
| `includeSkills` | boolean | Keep the skills array on each row. Default true. |
| `concurrency` | integer | Profiles processed in parallel. Six is the safe default. |
| `proxyConfiguration` | object | Apify proxy. Residential is required at any meaningful volume. |
***
### API call
```bash
curl -X POST \
"https://api.apify.com/v2/acts/YOUR_USER~linkedin-profile-scraper/runs?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella"
]
}'
```
***
### Pricing
The first three profiles per run are free so you can validate output before paying. After that, each profile row is charged. No surprise add on charges.
***
### FAQ
#### Do I need a LinkedIn account or cookie?
No. The actor only touches public profile pages. Your account is never touched.
#### What fields ship if a profile is partly hidden?
LinkedIn varies how much it shows anonymous viewers. Name, headline, location, current title, current company, profile photo, and summary ship reliably. Experience and education depth depends on what the public page renders.
#### Can I pass bare usernames instead of full URLs?
Yes. `williamhgates` and `/in/williamhgates` are accepted alongside the full `https://www.linkedin.com/in/williamhgates` form.
#### How fresh is the data?
Each run hits the live profile page, so headline, current role, and recent experience reflect what LinkedIn renders at scrape time. Schedule weekly runs to track changes over time.
#### Why is `connectionCount` capped at 500?
LinkedIn publicly displays connection counts as "500+" once a member crosses that threshold. The parsed value reflects exactly what LinkedIn shows.
#### Is scraping LinkedIn allowed?
This actor reads HTML any anonymous web visitor can see. Respect LinkedIn's terms and rate limit sensibly. Do not redistribute data you have no lawful basis to process.
***
### Related actors
- **LinkedIn Company Profile Scraper** — pull industry, headcount, HQ, and founded year for the company a contact works at
- **LinkedIn Profile & Company Post Tracker** — scrape posts from any profile or company without a cookie
- **LinkedIn Hiring Tracker & Salary Intelligence** — parsed salary, tech stack, and seniority on every job row
- **LinkedIn Pulse Articles Scraper** — long form articles by author or topic
- **Lead Enrichment Pipeline** — multi source enrichment for a list of company domains
# Actor input Schema
## `profileUrls` (type: `array`):
List of LinkedIn member URLs whose public profile facts you want to scrape. Examples: 'https://www.linkedin.com/in/williamhgates', 'https://www.linkedin.com/in/satyanadella'. Slug or full URL both accepted.
## `includeExperience` (type: `boolean`):
Pull the top experience items LinkedIn shows publicly. Each item ships with title, company, employment dates, and location when available.
## `includeEducation` (type: `boolean`):
Pull the top education entries LinkedIn shows publicly. Each entry ships with school, degree, field, and date range when available.
## `includeSkills` (type: `boolean`):
Pull the top skills LinkedIn shows publicly on the profile.
## `concurrency` (type: `integer`):
Number of profiles processed in parallel. Higher concurrency runs faster but increases proxy and detection risk. Six is a safe default.
## `proxyConfiguration` (type: `object`):
Apify proxy. Residential is required for LinkedIn at any meaningful volume.
## Actor input object example
```json
{
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08"
],
"includeExperience": true,
"includeEducation": true,
"includeSkills": true,
"concurrency": 6,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# 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 = {
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/linkedin-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 = {
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08",
],
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("scrapemint/linkedin-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 '{
"profileUrls": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call scrapemint/linkedin-profile-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapemint/linkedin-profile-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Profile Scraper",
"description": "Pull structured profile facts from any public LinkedIn member URL without a cookie or login. Each row carries name, headline, location, current company, current title, profile summary, top experience, top education, top skills, and profile photo. JSON. Pay per profile.",
"version": "0.1",
"x-build-id": "6dViLiDeTFZnsZA8I"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapemint~linkedin-profile-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapemint-linkedin-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/scrapemint~linkedin-profile-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapemint-linkedin-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/scrapemint~linkedin-profile-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapemint-linkedin-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",
"properties": {
"profileUrls": {
"title": "Profile URLs",
"type": "array",
"description": "List of LinkedIn member URLs whose public profile facts you want to scrape. Examples: 'https://www.linkedin.com/in/williamhgates', 'https://www.linkedin.com/in/satyanadella'. Slug or full URL both accepted.",
"default": [
"https://www.linkedin.com/in/williamhgates",
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08"
],
"items": {
"type": "string"
}
},
"includeExperience": {
"title": "Include experience",
"type": "boolean",
"description": "Pull the top experience items LinkedIn shows publicly. Each item ships with title, company, employment dates, and location when available.",
"default": true
},
"includeEducation": {
"title": "Include education",
"type": "boolean",
"description": "Pull the top education entries LinkedIn shows publicly. Each entry ships with school, degree, field, and date range when available.",
"default": true
},
"includeSkills": {
"title": "Include skills",
"type": "boolean",
"description": "Pull the top skills LinkedIn shows publicly on the profile.",
"default": true
},
"concurrency": {
"title": "Concurrency",
"minimum": 1,
"maximum": 20,
"type": "integer",
"description": "Number of profiles processed in parallel. Higher concurrency runs faster but increases proxy and detection risk. Six is a safe default.",
"default": 6
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Apify proxy. Residential is required for LinkedIn at any meaningful volume.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```