Best LinkedIn Scraper APIs in 2026 for Lead Data

Key takeaways:

• Proxycurl, the category leader, shut down on July 4, 2025 after LinkedIn sued it in federal court, so any shortlist written before then is out of date.
• Courts have held that scraping public pages likely does not violate the CFAA, but LinkedIn still wins on contract and fake-account claims, which is what actually ended Proxycurl.
• Pricing splits between per-record APIs like Coresignal at roughly $0.005 to $0.20 per record and per-seat automation like PhantomBuster from $69 per month.
• ColdIQ routes to LinkedIn-derived providers through one key from $99 per month, so you buy the data without operating the scrapers.

Search for a LinkedIn scraper API in 2026 and most of the results are stale. They recommend Proxycurl, which no longer exists. It shut down on July 4, 2025 after LinkedIn filed a federal lawsuit alleging it had created fake accounts to harvest profiles at scale, and the founders chose to close rather than fight Microsoft's legal budget. The team's successor company now states plainly on its own homepage that it does not scrape LinkedIn.

That single event reframes the whole category. The question is no longer just which API returns the most complete profile. It is which approach leaves you holding legal and operational risk, and which one puts a vendor between you and it.

This list covers the tools that are actually running in 2026, with verified pricing, an honest note on what each one does when LinkedIn changes its defenses, and a clear split between three different products that all get called the same thing. Where a vendor does not publish a price, that is stated rather than guessed.

What Is a LinkedIn Scraper API?

A LinkedIn scraper API returns structured data about people, companies, and jobs that originated on LinkedIn, delivered over HTTP as JSON instead of through a browser. You send a profile URL or a search query, and you get back fields your code can use.

The label covers three genuinely different products, and confusing them is the most expensive mistake in this category.

Dataset and database providers such as Coresignal and Bright Data maintain their own indexes assembled from public web sources, then sell you access. You query their copy, not LinkedIn, so nothing hits LinkedIn from your infrastructure and no account of yours is at risk. Freshness depends on their refresh cycle.

Live scraping infrastructure such as Apify and Scrapingdog fetches pages on demand, handling proxies, rendering, and blocking. Data is current, but you are the one initiating the request, which is where compliance questions land.

Account-based automation such as PhantomBuster and Unipile acts through a logged-in LinkedIn session, usually yours. This is the only category that can see connection-gated data or send messages, and the only one that can get a real account restricted.

Most teams building lead lists want the first category and reach for the third by accident, because it demos well.

The Legal Position, Briefly

This matters enough to state plainly before the list, because it drives the buying decision.

In hiQ Labs v. LinkedIn, the Ninth Circuit held that scraping publicly available pages likely does not constitute access "without authorization" under the Computer Fraud and Abuse Act. The court reaffirmed that holding in 2022 after the Supreme Court sent the case back for reconsideration in light of Van Buren v. United States, which narrowed the CFAA's reach. Public data, narrowly read, is not a computer-crime problem.

That is a much smaller shield than vendors imply. The CFAA is one statute among many, and hiQ itself later settled on terms that included a permanent injunction. LinkedIn's stronger cards are breach of contract under its user agreement and claims tied to fake accounts, and those are exactly what it played against Proxycurl. Creating accounts to scrape is a different act from reading a public page, and the case law protecting the second does not protect the first.

The practical translation is simple. Buying finished data from a provider that assembled it from public sources puts contractual exposure on that provider. Running automation through your own logged-in account puts it on you.

The Best LinkedIn Scraper APIs in 2026

The table below covers all three product types. Pricing is current as of July 2026 and taken from each vendor's own pricing page.

Ratings weigh legal posture and reliability alongside data quality, which is why the dataset providers outrank some better-known automation tools.

ColdIQ

Best for: Buying LinkedIn data without scraping

Overview: ColdIQ sells access to 40+ B2B data providers through one API key and a single credit balance, covering 700+ endpoints across people search, contact enrichment, work-email lookup, company intelligence, and hiring signals.

It belongs on this list because of what it does not do. ColdIQ runs no scrapers and holds no LinkedIn session. It routes your request to providers that already maintain LinkedIn-derived indexes, which means the profile data arrives without your infrastructure ever touching LinkedIn or your account carrying restriction risk.

That routing is the product. Instead of evaluating a dozen vendors on coverage, signing a dozen contracts, and rebuilding when one is sued or shuts down, you call one endpoint and the service selects a provider on fit, cost, and accuracy. Responses name the source and the credits consumed, so the per-record cost stays auditable.

Three interfaces ship on every plan: a REST API with a full OpenAPI spec, an MCP server that runs inside Claude Code, Codex, and Cursor, and plain-language agent chat.

Key features:

• One API key across 40+ providers, so a vendor shutting down is a routing change rather than a rebuild
• 700+ endpoints spanning people search, enrichment, work emails, phones, and company intelligence
• Automatic provider routing chosen on fit, cost, and accuracy rather than by you
• MCP server for Claude Code and other agents, so an agent can pull lead data directly
• Responses that return the source and credits consumed, keeping cost per record visible
• 100+ published Claude Code skills encoding full targeting and enrichment chains

Pricing: Starter is $99 per month for 2,000 credits, Pro $199 for 5,000, and Scale $499 for 15,000, with custom Enterprise volumes above. Annual billing takes 30% off, unused credits roll over for three months, and the playground is free with no credit card.

Pros: no scraping infrastructure to run, no LinkedIn account at risk, provider risk absorbed by the routing layer, cost per record visible in every response, MCP support for agents

Cons: it is an aggregation layer rather than its own index, so credits sit on top of provider economics; it cannot reach connection-gated data that only a logged-in session sees

How to start using it:

1. Open the free playground and run a people search without entering card details.
2. Create an account and generate an API key from the dashboard.
3. Call an enrichment endpoint with a company domain or a person's name, then read the `source` and `credits` fields to see which provider answered and what it cost.
4. Connect the MCP server to Claude Code if you want an agent to assemble lists rather than writing the calls yourself.
5. Match a plan to your monthly record volume and pipe the JSON into your CRM or sequencer.

Why it's a good LinkedIn scraper API alternative: It delivers the outcome people want from scraping, which is structured profile and company data, without the operational and legal overhead of running scrapers.

Final verdict: The strongest option for teams whose goal is lead data rather than scraping as such. It will not replace an account-based tool if you specifically need connection-gated fields or InMail sending, and it does not pretend otherwise. For everyone else, routing through one vendor is the lower-risk version of what Proxycurl's customers were buying.

CTA: Get started free in the playground, no card required.

Coresignal

Overview: Coresignal maintains its own index built from 15+ public web sources, covering 70M+ companies, 895M+ employee records, and 468M+ job postings. You query their database rather than LinkedIn, which removes the operational risk entirely.

Key features:

• Database APIs over company, employee, and job-posting records
• Separate Collect and Search credits so query cost and record cost are distinct
• Historical headcount API and employee webhooks on the top tier

Pricing: A free tier gives 200 Collect and 400 Search credits valid for seven days. Starter is $49 per month, Pro $800, and Premium $1,500, with effective rates falling from roughly $0.196 per record at Starter to as little as $0.005 at Premium. Paying yearly saves 20%. Bulk datasets start at $1,000 or more per month with no free option.

Pros: very large index, no scraping risk on your side, rates improve sharply with volume

Cons: the jump from $49 to $800 is steep, free credits expire in seven days, multi-source company records consume double credits

Why it's a good LinkedIn scraping API: It is the cleanest way to get employee and firmographic data at volume without operating any infrastructure.

Final verdict: The best pick for teams that need bulk records and can commit to volume. Below a few thousand records a month the Starter tier is fine, but the price ladder above it is unusually steep.

Bright Data

Overview: Bright Data sells prebuilt datasets alongside scraping infrastructure. Its B2B catalog includes LinkedIn People Profiles, LinkedIn Company Information, and LinkedIn Job Listings, delivered as files rather than per-request lookups.

Key features:

• Prebuilt LinkedIn people, company, and job datasets
• Refresh-rate discounts reaching 80% for monthly delivery
• Scraping infrastructure available alongside the dataset marketplace

Pricing: The dataset marketplace base rate is $2.50 per 1,000 records, with volume tiers from 100,000 records up to full-database delivery. Refresh discounts run 25% biannual, 50% quarterly, and 80% monthly. Exact per-tier totals are not published, and a minimum monthly commitment is billed at the start of the month.

Pros: genuine enterprise scale, strong compliance posture, steep discounts for recurring refreshes

Cons: per-tier pricing is not published, minimum commitments rule out small teams, heavier procurement than a self-serve API

Why it's a good LinkedIn web scraping API: For bulk delivery of millions of records, file-based datasets beat per-request APIs on both cost and throughput.

Final verdict: Right for enterprises with procurement processes and real volume. If you want to test an idea this week, the commitment structure makes it the wrong starting point.

Apify

Overview: Apify is a developer platform for running scrapers, called Actors, with proxies, scheduling, and storage handled for you. Its store carries multiple LinkedIn scrapers built by third parties.

Key features:

• Actor marketplace with several LinkedIn-focused scrapers
• Managed proxies, scheduling, storage, and concurrency controls
• Full API and SDKs for embedding runs in your own pipeline

Pricing: The free plan includes $5 of usage. Starter is $29 per month plus pay-as-you-go, Scale $199, and Business $999. Compute units cost $0.20 on Free and Starter, $0.16 on Scale, and $0.13 on Business.

Pros: flexible and genuinely developer-friendly, low entry cost, large library of prebuilt scrapers

Cons: Actor quality and upkeep vary by author, compute-unit billing is hard to forecast, you carry the compliance question

Why it's a good LinkedIn API for scraping: It removes the infrastructure work while leaving you full control over scraping logic.

Final verdict: A strong fit for engineering teams that want to own the pipeline. Check when your chosen Actor was last updated before depending on it, because an abandoned scraper breaks the first time LinkedIn changes its markup.

Unipile

Overview: Unipile is a unified messaging and account API. It connects a real LinkedIn account and exposes profiles, messages, chats, InMail, posts, and engagement through 100+ endpoints.

Key features:

• 100+ unified endpoints across LinkedIn and other channels
• Unlimited API calls with no usage-based fees, subject to provider rate limits
• Real-time webhooks and hosted authentication

Pricing: Pay-as-you-go with no commitment, starting at €49 per month for up to 10 connected accounts, then €5.00 per account per month from 11 to 50 accounts, with lower rates above that and custom pricing past 1,000. A 7-day free trial needs no credit card.

Pros: unlimited API calls, covers messaging as well as data, transparent per-account pricing

Cons: operates through your logged-in account, so restriction risk is yours; priced per account rather than per record; euro-denominated billing

Why it's a good LinkedIn scraper API: Nothing else here combines profile access with the ability to actually message the person you just enriched.

Final verdict: The right tool when outreach and data collection are the same workflow. Treat the account risk as real and connect accounts you can afford to lose.

ScrapIn

Overview: ScrapIn focuses narrowly on real-time LinkedIn profile and company lookups, returning fresh data on request rather than serving a cached index.

Key features:

• Real-time profile and company data rather than cached records
• Pay-as-you-go credits valid for 12 months
• Guaranteed daily rate limits and high concurrency on Enterprise

Pricing: A 7-day full-access trial costs $30. Pay-as-you-go starts at $500 with no commitment and 12-month validity. Enterprise is custom with a 12-month term, guaranteed rate limits, and Slack support. Exact credit counts per tier are not published.

Pros: genuinely real-time data, credits valid a full year, no commitment on the pay-as-you-go tier

Cons: no free trial, $500 minimum after the trial, credit allotments are not published

Why it's a good LinkedIn scraping API: Freshness is its whole proposition, which matters when a stale job title breaks your personalization.

Final verdict: Worth the $30 trial if freshness is your binding constraint. The unpublished credit counts make it hard to compare on price until you are already inside.

Wiza

Overview: Wiza turns LinkedIn and Sales Navigator searches into exportable contact lists with verified emails and phone numbers. It is contact-data-first rather than profile-data-first.

Key features:

• Sales Navigator search export with email and phone reveal
• Pay-per-valid-result billing on the entry tier
• Chrome extension alongside the API for manual workflows

Pricing: A free tier gives 20 valid emails and 5 phones. Starter is $49 per user per month for 100 emails and 100 phones, then $0.15 per email and $0.35 per phone. Email is $83 per user per month billed annually or $99 monthly, and Email + Phone is $166 annually or $199 monthly. API access is limited to the Email + Phone plan and the custom Team plan.

Pros: strong contact-data coverage, usable free tier, transparent per-result overage rates

Cons: API gated to the top plans, per-seat pricing, accuracy claims are vendor-cited rather than independent

Why it's a good LinkedIn scraper API: It closes the last mile that profile data leaves open, which is the reachable email address.

Final verdict: Buy it for contact data, not profile data. Just confirm you are on a plan that includes API access before building anything against it.

PhantomBuster

Overview: PhantomBuster is the best-known no-code option, with 100+ prebuilt automations that chain LinkedIn actions together on a schedule. It runs through your logged-in session.

Key features:

• 100+ prebuilt automations covering scraping and outreach sequences
• Execution-time pricing with up to 100 workspace members on every plan
• Scheduling and chaining without writing code

Pricing: A 14-day trial needs no card and includes 2 hours of execution, though exports are capped at 10 rows. The residual free plan gives 30 minutes a month. Start is $69 per month ($56 annually) for 20 hours, Grow $159 ($128) for 80 hours, and Scale $439 ($352) for 300 hours. Annual billing saves 20% and credits reset monthly with no rollover.

Pros: no code required, team seats included at no extra cost, large automation library

Cons: runs through your own account so restriction risk is yours, credits expire monthly, execution-hour budgeting is unintuitive

Why it's a good LinkedIn scraper API: It is the fastest path from idea to running workflow for teams without engineers.

Final verdict: Convenient and genuinely popular, but it is the highest-risk option here for account safety. Use a secondary account and keep volumes conservative.

Scrapingdog

Overview: Scrapingdog offers a dedicated LinkedIn endpoint within a broader scraping API, handling proxies and blocking so you send a URL and get structured data back.

Key features:

• Dedicated LinkedIn scraping endpoint alongside general web scraping
• Proxy rotation and block handling managed for you
• Simple per-plan pricing with a wide tier ladder

Pricing: A free tier is available and Lite starts at $40 per month, with Business at $500, Corporate at $2,000, and a long ladder of higher tiers running into five figures for very large volumes.

Pros: cheap entry point, straightforward API, generous tier range for scaling

Cons: returns page data rather than enriched records, no contact-data layer, you initiate the requests

Why it's a good LinkedIn web scraping API: At $40 per month it is the cheapest realistic way to fetch LinkedIn pages programmatically.

Final verdict: Good value if you want raw pages and will do your own parsing and enrichment. Not the tool if you want finished lead records.

Lix

Overview: Lix provides a LinkedIn API for programmatic profile access, with people search, company search, job search, and profile enrichment endpoints, plus an export-oriented interface.

Key features:

• People, company, and job search endpoints plus profile enrichment
• Free tier with 50 credits a month and 1,000 search-level exports
• New API users get 10 free credits to test

Pricing: Starter is free with 50 credits a month, 1,000 search-level exports, and three included users. Paid Leads and Data Plus tiers charge $0.15 per additional email and raise export limits. API credit packs run $49 for 500 credits on Standard or $49 for 2,500 on Organization.

Pros: genuinely free entry tier, three users included at no cost, clear per-email overage

Cons: small credit packs, headline plan prices vary rather than being fixed, smaller scale than the dataset providers

Why it's a good LinkedIn API for scraping: The free tier lets you validate whether the data shape fits before spending anything.

Final verdict: A reasonable starting point for small teams and prototypes. Volume buyers will outgrow the credit packs quickly.

NinjaPear

Overview: NinjaPear is the successor company built by the Proxycurl team after that product closed. It sells B2B intelligence covering company details, funding, employee profiles, and work-email lookups, aggregated from public web sources.

Key features:

• Company, funding, competitor, and employee-profile endpoints
• Work-email lookup and email validation alongside profile data
• Credits shared across products, with a documented 50 requests per minute rate limit

Pricing: A 3-day free trial includes 10 credits with no card. Starter is $49 per month for 2,500 credits ($0.0196 each), Growth $299 for 25,000 ($0.0120), Pro $899 for 89,900 ($0.0100), and Ultra $1,899 for 211,000 ($0.0090). Enterprise is quote-based. Subscription credits expire at the end of each billing period.

Pros: transparent per-credit rates at every tier, deliberately conservative sourcing, familiar API shape for Proxycurl migrants

Cons: subscription credits expire monthly, it is explicitly not a LinkedIn scraper, the company is young in its current form

Why it's a good LinkedIn scraper API alternative: It answers the question most searchers actually have, which is what to use now that Proxycurl is gone.

Final verdict: The natural first stop for anyone migrating off Proxycurl. Judge it on its public-web coverage rather than expecting LinkedIn parity, because the company is explicit that parity is not what it offers.

How We Chose the Best LinkedIn Scraper APIs

Three tests decided the list and the ratings.

First, does the tool still exist and does its LinkedIn capability verify? Proxycurl is closed. HasData and Piloterr publish no LinkedIn endpoint despite appearing in roundups, so neither is listed.

Second, where does the risk sit? Tools serving their own index rank above tools running through your logged-in account, because the failure modes differ by an order of magnitude. A dataset provider going down costs you a day; a restricted account costs you a sales channel.

Third, is the pricing published? Every price here comes from the vendor's own page, checked in July 2026. Where a vendor publishes no per-tier figures, as Bright Data and ScrapIn do not, the entry says so.

What to Look For in a LinkedIn Scraping API

Data source is the first question. Ask whether the vendor queries its own index or fetches LinkedIn live on your behalf. That single answer determines your legal exposure, your latency, and whether your account can be restricted, and it is usually buried in documentation.

Freshness and refresh cadence decide whether personalization works. A cached index that refreshes quarterly will confidently return the job someone left eight months ago. For job-change triggers, ask for the refresh interval in writing; for static firmographics, cached data is perfectly adequate and cheaper.

Credit mechanics hide most of the real cost. Coresignal charges double for multi-source company records, Wiza prices phones above twice its email rate, and NinjaPear expires subscription credits each billing period. Identical headline rates can differ by half on the same workload.

Rate limits and concurrency determine throughput more than price does. A cheap plan capped at a few requests per second cannot backfill 200,000 profiles in a weekend regardless of your credit balance, so check the ceiling at your tier before modeling the job.

Failure behavior is worth testing on day one. Confirm whether you are charged for a lookup that returns nothing, because a provider that bills for misses on a list with 40% coverage costs far more than its rate card implies.

How Much Do LinkedIn Scraper APIs Cost?

Three pricing models compete here, and comparing across them is where budgets go wrong.

Per-record pricing is the easiest to forecast and the model most dataset providers use. Coresignal spans roughly $0.196 per record at $49 per month down to about $0.005 at Premium, which is a fortyfold spread driven entirely by commitment. NinjaPear's ladder is tighter, running $0.0196 down to $0.0090.

Per-request infrastructure looks cheapest and often is not, because the price buys a page rather than a finished record. Scrapingdog at $40 per month and Apify from $29 plus compute both leave parsing and enrichment as your problem, and that engineering time rarely appears in the comparison.

Per-account automation prices by seat, which decouples cost from volume entirely. PhantomBuster from $69 per month and Unipile from €49 make sense when you are working a few thousand targets through a handful of accounts, and stop making sense the moment you need a million records.

The number most teams should calculate is cost per usable record, not cost per call. A $40 plan that returns unparsed pages at 60% coverage is more expensive than a $99 plan returning enriched records at 90%, and the gap widens as the list grows.

How Do You Choose the Right LinkedIn API?

Start from what the data is for, since that maps cleanly onto the three product types.

If you need lead records at volume and never need to message through LinkedIn, buy from an index. Coresignal for bulk employee and company data, Bright Data if you are enterprise and want file delivery, or ColdIQ if you would rather route across providers than pick one and hope it survives.

If you need messaging and data in one flow, you need an account-based tool, and Unipile or PhantomBuster are the honest choices. Accept that this puts a real account at risk and plan accordingly, which in practice means a dedicated account and conservative volumes.

If you have engineers and want control, Apify or Scrapingdog give you the infrastructure without the abstractions. Budget for maintenance, because scrapers break when LinkedIn ships changes and somebody has to fix them.

If you are migrating off Proxycurl specifically, NinjaPear is the closest thing to a continuation, and ColdIQ is the option that spreads the risk so the next shutdown is not your problem. The concern is common enough that one r/n8n user described losing a working sales-automation pipeline and asking the community for a replacement that could still enrich profiles, track job changes, and pull company data affordably. That is one person's account rather than a survey, but it captures the migration problem precisely: the gap left behind was never a single feature, it was a bundle.

Budget sets the floor. Below $100 a month, Lix's free tier, Scrapingdog at $40, or Coresignal at $49 are the realistic options. Above $500, the dataset providers become clearly better value than stacking automation seats.

Where to Start With LinkedIn Lead Data

The decision is less about which vendor is best and more about which risk you are willing to hold. Proxycurl's customers learned that the hard way, on a legal outcome rather than a technical one.

Start with an index-based provider so nothing touches LinkedIn from your side. Add an account-based tool only if you need connection-gated data or in-platform messaging, and isolate it on an account you can afford to lose. Keep your own scraping infrastructure as a last resort.

Above all, avoid single-vendor dependency on a category this volatile. The tools worth using in 2026 are the ones that will still be answering requests in 2027, and the honest answer is that nobody knows which those are.

If you want to see what is callable before committing, ColdIQ's data sources directory lists the providers behind the routing layer, and the MCP server is worth a look if you want an agent pulling this data directly. For the wider category, our roundups of data scraping tools and web scraping APIs cover the non-LinkedIn options, while LinkedIn prospecting tools and our guide to prospecting on LinkedIn cover the workflow the data feeds. If you would rather stay manual, these Chrome extensions do the job without an API at all.