# Fast LinkedIn Profile Scraper: B2B Leads & Emails (No Cookies) (`rbbscrap/fast-linkedin-profile-scraper`) Actor

Ultra-fast LinkedIn profile scraper with zero cookie requirements. Extract job titles, current companies, career history, education, skills, and predicted corporate emails on 256MB RAM.

- **URL**: https://apify.com/rbbscrap/fast-linkedin-profile-scraper.md
- **Developed by:** [Hector](https://apify.com/rbbscrap) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.50 / 1,000 profile 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/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

## 🚀 Fast LinkedIn Profile Scraper: B2B Leads & Emails (No Cookies)

Extract verified LinkedIn profiles, job titles, current companies, full career history, education, skills, and predicted corporate emails with **zero cookies required**.

***

### ⚡ Points Forts & Avantages Clés (Reverse-Engineered vs HarvestAPI)

1. **Zero-Cookie / No Login Requis :** Vous n'avez jamais besoin de renseigner votre cookie de session `li_at`. Aucun risque de bannissement de compte LinkedIn.
2. **Enrichissement Email Professionnel Automatique :** Génération des adresses emails professionnelles vérifiées (`prenom.nom@societe.com`, etc.) à partir du poste et de l'entreprise actuelle.
3. **Architecture Micro-Conteneur 256 Mo :** Fonctionne à la vitesse de l'éclair en pure requête HTTP/2 sans aucun navigateur lourd.
4. **Carrière & Formation Complètes :** Extraction de l'historique complet des expériences (`worksFor`), dates, postes et universités (`alumniOf`).
5. **Tarif 3x Moins Cher :** Calibré à seulement **$1.80 / 1 000 profils** (au lieu de $5.00/1k chez HarvestAPI).

***

### 📥 Exemple d'Entrée (JSON)

```json
{
  "urls": [
    "https://www.linkedin.com/in/satyanadella"
  ],
  "predictCorporateEmails": true,
  "maxProfiles": 50
}
```

***

### 📤 Exemple de Sortie (Dataset)

```json
{
  "profileUrl": "https://www.linkedin.com/in/satyanadella",
  "fullName": "Satya Nadella",
  "headline": "Chairman and CEO at Microsoft",
  "currentCompany": "Microsoft",
  "location": "Redmond, Washington, United States",
  "followers": 12274259,
  "predictedEmails": [
    "satya.nadella@microsoft.com",
    "snadella@microsoft.com"
  ],
  "experiences": [
    {
      "company": "Microsoft",
      "startDate": "2014-02",
      "endDate": "Present"
    }
  ],
  "education": [
    {
      "institution": "The University of Chicago Booth School of Business",
      "startDate": 1994,
      "endDate": 1996
    }
  ],
  "zeroCookieMode": true,
  "scrapedAt": "2026-11-01T12:00:00.000Z"
}
```

# Actor input Schema

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

List of direct LinkedIn profile URLs (e.g. https://www.linkedin.com/in/satyanadella).

## `queries` (type: `array`):

Public identifiers or usernames to scrape (e.g. 'satyanadella', 'williamhgates').

## `predictCorporateEmails` (type: `boolean`):

Automatically predict corporate email addresses based on current employer domain.

## `maxProfiles` (type: `integer`):

Maximum number of profiles to extract in this run.

## `proxyConfiguration` (type: `object`):

Apify Proxy or custom proxies to bypass rate-limits.

## Actor input object example

```json
{
  "urls": [
    "https://www.linkedin.com/in/satyanadella"
  ],
  "predictCorporateEmails": true,
  "maxProfiles": 100,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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 = {
    "urls": [
        "https://www.linkedin.com/in/satyanadella"
    ],
    "predictCorporateEmails": true,
    "maxProfiles": 100,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("rbbscrap/fast-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "urls": ["https://www.linkedin.com/in/satyanadella"],
    "predictCorporateEmails": True,
    "maxProfiles": 100,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("rbbscrap/fast-linkedin-profile-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 '{
  "urls": [
    "https://www.linkedin.com/in/satyanadella"
  ],
  "predictCorporateEmails": true,
  "maxProfiles": 100,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call rbbscrap/fast-linkedin-profile-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rbbscrap/fast-linkedin-profile-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/h8bTyFgg4EooddE9k/builds/wQzfU7S7J2fNhhiaV/openapi.json