LinkedIn Profile Scraper — No Cookies

Build purpose-sized LinkedIn profile datasets by choosing which public profile sections each run should include.

ToolzerHub maintains LinkedIn Pro Profile Scraper for enrichment workflows that need control over record depth. Submit usernames or profile URLs, select the optional sections your workflow actually needs, and receive structured rows in an Apify dataset.

Start with the destination system

The best profile dataset is not automatically the largest one. A recruiting review may need experience, education, certifications, and bio; a routing step may only need identity fields; a research archive may also need publications, honors, volunteer work, interests, and audience counts.

The input exposes those choices directly so organizations can define the record before running the collection job.

Configure a reusable enrichment policy

Use the same input for a one-time batch, a schedule, or an API-triggered workflow. The profile section switches are explicit, which makes the configuration reviewable and repeatable across an organization.

Field	Type	Required	Description
username	array	Yes	Seed LinkedIn profile usernames or /in/ profile URLs to fetch full profile details for.
include_follower_and_connection	boolean	No	Include follower and connection counts. Adds one Profile Enrichment charge per returned profile.
include_experiences	boolean	No	Include work experience. Adds one Profile Enrichment charge per returned profile.
include_skills	boolean	No	Include profile skills. Adds one Profile Enrichment charge per returned profile.
include_certifications	boolean	No	Include certifications. Adds one Profile Enrichment charge per returned profile.
include_publications	boolean	No	Include publications. Adds one Profile Enrichment charge per returned profile.
include_educations	boolean	No	Include education history. Adds one Profile Enrichment charge per returned profile.
include_volunteers	boolean	No	Include volunteer experience. Adds one Profile Enrichment charge per returned profile.
include_honors	boolean	No	Include honors and awards. Adds one Profile Enrichment charge per returned profile.
include_interests	boolean	No	Include interests. Adds one Profile Enrichment charge per returned profile.
include_bio	boolean	No	Include the profile bio/about section. Adds one Profile Enrichment charge per returned profile.

Example: begin with a bounded batch

{
  "username": [
    "williamhgates"
  ]
}

The stable columns and the expandable payload

Every result keeps common profile identifiers—such as the seed username, record ID, URN, public identifier, name, and headline—in predictable columns. Additional selected profile material is carried in the structured data object so an organization can retain richer sections without flattening unlike records into misleading columns.

Field	Type	Description
username	string	Seed username used to fetch this profile.
id	string	Record ID.
urn	string	LinkedIn URN for the record.
public_identifier	string	Public LinkedIn identifier (username/handle) for the record.
full_name	string	Full name shown on the profile.
headline	string	Current headline shown on the profile.
data	object	Additional fields that are not explicitly modeled above.

Compact output preview

{
  "username": "williamhgates",
  "full_name": "Bill Gates",
  "headline": "Co-chair, Gates Foundation"
}

Profiles can expose different amounts of public information. Consumers should expect optional sections to be absent when they were not selected or were not publicly available.

Pricing and rollout discipline

This Actor charges once for each successful profile saved to the dataset. Every enabled optional profile section adds one Profile Enrichment event for that profile. Failed profiles are not charged as results or enrichments; current tier prices are shown on the Actor Pricing tab.

Apify's free credits may cover small test runs and up to the free result allowance configured for the Actor.

ToolzerHub recommends validating the selected switches and downstream field mapping with a small username list, then saving that input as the approved configuration for larger or scheduled runs.

Put profile enrichment inside your stack

Python client

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")
run = client.actor("toolzerhub/linkedin-profile-scraper").call(run_input={
    "username": [
        "williamhgates"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript client

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" });
const run = await client.actor("toolzerhub/linkedin-profile-scraper").call({
  "username": [
    "williamhgates"
  ]
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Data responsibility

This Actor extracts publicly available LinkedIn data. It should not be used to collect private data, bypass access controls, or contact people in ways that violate privacy laws, LinkedIn terms, or your own compliance obligations. Personal data may be protected by GDPR and similar laws. If you are unsure, consult a qualified lawyer.

Complementary ToolzerHub Actors

• LinkedIn People Search Scraper — No Cookies — Search LinkedIn people without providing LinkedIn cookies. Find profiles by name, title, company, school, location, industry, and other filters, then paginate structured results.
• LinkedIn Company Scraper — No Cookies — Extract complete public LinkedIn company pages from company handles or IDs without providing LinkedIn cookies. Batch company inputs and receive structured company details for every result.
• LinkedIn Company Employees Scraper — No Cookies — Collect public employees listed on a LinkedIn company page without providing LinkedIn cookies. Enter a company ID, paginate automatically, and export structured employee profiles.

ToolzerHub support

Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests.

Contact: contact@toolzerhub.com