Proxycurl Is Gone: Best LinkedIn Data API Alternatives in 2026 (and How to Migrate)

Proxycurl, for years one of the most popular LinkedIn data APIs, shut down in 2025 after LinkedIn sued the company behind it. If your pipeline broke overnight, this guide gives you the accurate story (the dates and the case, not the rumors), the real lesson for choosing your next vendor, an honest comparison of the live alternatives by model, and a concrete migration path. No gloating, no single-product hard sell – just what happened and what to do next.

The short version. For a like-for-like "profile URL in, JSON out" replacement, a real-time scraper (ScrapIn, Apify, Bright Data) is the closest drop-in. For bulk enrichment, a dataset provider (Coresignal, People Data Labs) fits. If you want live data plus the ability to act – and no shared scraped database that a court can order deleted – an account-based API (Linked API, Unipile) is the durable play. The thing that actually killed Proxycurl – fake accounts and a central scraped index – is the thing not to repeat.

What happened to Proxycurl

On January 24, 2025, LinkedIn sued the company behind Proxycurl (Nubela) in the U.S. District Court for the Northern District of California – LinkedIn Corp. v. Nubela Pte. Ltd., case 3:25-cv-00828. The complaint brought six claims, including breach of contract, fraud, violation of the Computer Fraud and Abuse Act (CFAA), California's Unfair Competition Law, a Lanham Act claim, and misappropriation.

The core allegation was not simply "they used LinkedIn data." It was that Proxycurl created hundreds of thousands of fake accounts to scrape millions of profiles, including non-public data, and resold that data through its API. The case settled in mid-2025 with a court-entered permanent injunction; Proxycurl posted its goodbye in July 2025 and wound the service down, with customers notified and data slated for deletion.

To its credit, Proxycurl's founder was candid afterward. He wrote that the business had reached roughly $10M in revenue, that about half of it came from scraping LinkedIn – "exactly why the legal risk was existential" – and that there was "no winning in fighting this" against a company with an effectively unlimited legal budget. The team has since pivoted to a new product, NinjaPear, that explicitly does not scrape LinkedIn.

The real lesson for picking your next API

It is tempting to read this as "LinkedIn data is radioactive, stay away." That is the wrong takeaway. The fatal combination was specific: fake accounts at scale, scraping non-public data, packaged as a central database and resold. Each of those is a separate aggravating factor, and together they made the case easy to bring.

The legal backdrop is more nuanced than the headlines. Scraping genuinely public data is not automatically illegal in the US – that is the takeaway from hiQ Labs v. LinkedIn. But the moment you spin up fake accounts, reach non-public data, or breach LinkedIn's User Agreement at scale, you are in CFAA and contract territory. (We cover the full four-layer legal model in our guide to scraping LinkedIn.)

For you as a buyer, the practical lesson is about continuity risk. A provider whose entire business is a central, scraped index of LinkedIn is one injunction away from gone – and that injunction can require deleting the very data you depend on, with little notice. Vendor selection now has to weigh "will this still exist, and will my data survive, in twelve months?" alongside price and coverage.

The live alternatives, by model

The LinkedIn data API landscape splits into three models. Most "Proxycurl alternative" listicles blur them together and then crown whichever product the author sells. Here they are honestly, with the trade-offs that matter.

Real-time scrapers are the closest drop-in for Proxycurl's bread-and-butter "give a profile URL, get JSON." ScrapIn (now merged into Reverse Contact) and Apify's LinkedIn actors are the usual developer picks; Bright Data is the enterprise-scale option with the strongest legal track record. You hand over a URL, they manage proxies and return structured data – and they carry the scraping risk.

Dataset providers like Coresignal and People Data Labs sell scale: hundreds of millions of records you can query or buy in bulk. They replace Proxycurl's search and enrichment use case, not real-time single lookups, and the trade-off is freshness – records are often months or years out of date between refreshes.

Account-based APIs work differently: they drive your own authenticated LinkedIn account in a cloud browser. There is no shared scraped index for a court to seize, and you can act (connect, message, react), not just read. The honest caveat: the risk shifts to your account and LinkedIn's terms, and throughput is bounded by your account's daily limits – it is not a bulk firehose. This is the account-based model we build at Linked API.

Map your Proxycurl endpoints to a replacement

Proxycurl exposed around 21 endpoints. Here is where each group goes now:

One honest note on contact data: the email and phone endpoints were always the legally hottest part of Proxycurl. Personal contact details are not something you should extract from LinkedIn directly – source them from a consented B2B enrichment provider instead. We explain why in the scraping guide.

Migrating to an account-based API

If you used Proxycurl for live profile reads and want control rather than a shared index, the account-based path maps cleanly. The Person Profile endpoint – a URL in, structured JSON out – becomes a single call against your own account. Install the SDK:

# Node.js
npm install -S @linkedapi/node

# Python
pip install linkedapi

Then fetch a profile by URL, the direct analog of Proxycurl's Person Profile endpoint:

import LinkedApi from '@linkedapi/node';

const linkedapi = new LinkedApi({
  linkedApiToken: process.env.LINKED_API_TOKEN,
  identificationToken: process.env.IDENTIFICATION_TOKEN,
});

const profile = await linkedapi.fetchPerson.execute({
  personUrl: 'https://www.linkedin.com/in/jane-doe',
  retrieveExperience: true,
  retrieveSkills: true,
});

const { data } = await linkedapi.fetchPerson.result(profile.workflowId);
console.log(data?.name, data?.position, data?.followersCount);

from linkedapi import LinkedApi, LinkedApiConfig, FetchPersonParams

linkedapi = LinkedApi(
    LinkedApiConfig(
        linked_api_token="your-linked-api-token",
        identification_token="your-identification-token",
    )
)

profile = linkedapi.fetch_person.execute(
    FetchPersonParams(
        person_url="https://www.linkedin.com/in/jane-doe",
        retrieve_experience=True,
        retrieve_skills=True,
    )
)

data = linkedapi.fetch_person.result(profile.workflow_id).data
print(data.name, data.position, data.followers_count)

The same execute then result pattern covers people search and company data. Grab your tokens from the installation guide to start.

A one-day migration checklist

1. Put a thin interface in front of your data source so you can swap providers without touching the rest of the app. Proxycurl taught everyone why this matters.
2. Pick a model by job: live single-profile reads to a real-time scraper, bulk firmographics to a dataset, your-own-account reads plus actions to an account-based API.
3. Map your fields. Most providers return the same core profile shape; normalize names once at the boundary.
4. Move contact lookups to consented enrichment rather than direct extraction.
5. Backfill any records you lost when Proxycurl went dark.
6. Handle limits. Real-time and dataset APIs have rate limits; account-based APIs surface a limit error when you would exceed your account's safe pace.

Frequently Asked Questions (FAQ)

Were you using Proxycurl for live profile reads and the ability to act? Linked API runs your own authenticated account and returns clean JSON for people, companies, posts, and search – with no shared scraped database to disappear overnight.