30 (+1) Top LinkedIn Scrapers for 2026 with Pros & Cons

After testing, buying, breaking, and in one case getting sued around this category, my short answer is this: most LinkedIn scrapers still work in 2026, but many are worse businesses than they are tools. If you just want the shortlist, Proxycurl was the old API-first favorite, but Proxycurl API has been sunset and the founder behind it is now building NinjaPear, which is not a LinkedIn scraper at all. For teams that still insist on scraping LinkedIn, PhantomBuster, Evaboot, People Data Labs, and Coresignal are still alive. For teams that want the commercial outcome without the LinkedIn liability, NinjaPear is the more durable bet.

That comment is blunt, and unfortunately, it is directionally right.

I am not going to rewrite this piece from scratch because the original structure was useful. I am going to do the much more practical thing: update it in place for 2026, fix the censored "Professional Social Network" nonsense, mark what is dead, and tell you where the legal landmines actually are.

A few 2026 updates before we start:

• Proxycurl API has been sunset. I kept the original sections where they still help explain the category, but if you are reading this in 2026, treat Proxycurl as historical context, not a live recommendation.
• The founder behind Proxycurl is now building NinjaPear. NinjaPear is a competitive intelligence and B2B data platform, not a LinkedIn automation tool.
• iScraper is dead. It got sued by LinkedIn. I added it as the "+1" because pretending dead tools never existed is how people repeat avoidable mistakes.
• I checked the major tools below for 2026 status. Where pricing or positioning changed, I updated it.

Welcome to the only guide on LinkedIn scrapers you will ever need. In this article, I will go through:

• 30+1 of the best LinkedIn scraping tools in 2026, categorized based on their nature.
• Pros and cons of each scraper.
• How to find the best LinkedIn scraper for you.
• Whether LinkedIn scraping is legal.
• My updated recommendation, including a bonus non-LinkedIn alternative.
• Final thoughts.

I'll start with an overview of all the LinkedIn scraper categories. This still matters because most buyers make the same mistake I made years ago: comparing an automation extension to an API vendor to a bulk dataset seller as though they are the same product. They are not.

LinkedIn scraper categories with features and suitability

Now, let's look at each of our 31 entrants in the list. Each of these LinkedIn scrapers is categorized and weighed based on price, free version availability, and one more thing I care a lot more about in 2026: business durability.

List of all 31 LinkedIn scrapers categorized into six major groups, plus one dead tool worth studying

Full-scale enterprise LinkedIn scrapers

These scrapers are built for larger companies that need scale, enrichment, analytics, and integrations. In practice, this category splits into two camps:

1. API-first vendors that want to sit inside your product or workflow.
2. Database vendors that already collected the data and want to sell access to it.

That distinction matters because the tradeoff is usually freshness vs convenience.

1. Proxycurl, sunset but worth understanding

2026 update: Proxycurl API has been sunset. I am retaining this section because the original article relied on it heavily and because Proxycurl shaped this category for a few years. But if you are evaluating tools today, skip ahead to NinjaPear for the modern Nubela product, or to the other live vendors below.

The biggest reason people used Proxycurl was that it was a versatile API designed to be built into an existing system or workflow. No VPNs. No proxy juggling. No rotating pile of LinkedIn accounts. Just an API call and structured B2B data.

That was always the real appeal. Not that it was magical. Just that it removed a lot of the gross operational plumbing.

It was also developer-friendly, and yes, the number of endpoints could be intimidating if you were non-technical. That part of the original article was fair.

The other thing Proxycurl got right was this idea that buyers care about freshness controls, not just raw access. That is still one of the most useful lenses for comparing vendors today.

Proxycurl Pros

• API-first and easy to integrate.
• Strong data depth for person and company enrichment.
• Historically good freshness controls.
• Built for scale, not one-off CSV exports.

Proxycurl Cons

• Sunset, so not a live option in 2026.
• Better for developers than for solo operators.
• If you wanted a Chrome extension and instant CSVs, it was never really that product.

Proxycurl Pricing

Plans	Details
Status	Sunset
Recommendation in 2026	Historical context only

2. NinjaPear, the bonus alternative

NinjaPear is here because pretending every buyer must scrape LinkedIn is lazy thinking.

NinjaPear is not a LinkedIn scraper. It is not a browser automation tool. It does not ask you to install a Chrome extension and pray your account survives. It is a competitive intelligence and B2B data platform that gives you a lot of the commercial wins people chase with LinkedIn automation, without putting your business on top of LinkedIn-derived data.

That difference is not semantic. It is the whole point.

What can you do with NinjaPear instead of LinkedIn scraping?

• Find a company's customers with the Customer API
• Track competitor and prospect account changes with the Monitor API
• Enrich people and companies from public web data
• Build prospect lists in Prospector
• Pull company details, work emails, employee count, and competitor data without touching LinkedIn

When I was running FluxoMetric, I would have killed for this exact category of product. Not because it is morally superior. Because it is operationally saner.

LinkedIn automation is usually trying to approximate one of these outcomes:

• figure out who matters at an account
• figure out what changed at an account
• figure out who buys from whom
• figure out when to reach out

NinjaPear does those things directly.

NinjaPear Pros

• Avoids LinkedIn account automation risk entirely.
• Gives you competitive intelligence data LinkedIn does not really provide well anyway.
• API, spreadsheet, and UI workflows are all there.
• Transparent usage-based pricing, no big enterprise minimums.

NinjaPear Cons

• Not a LinkedIn scraper, so if your requirement is literally "give me the LinkedIn profile DOM as JSON," this is not that.
• Newer product category, which means some buyers still need to unlearn old habits.

NinjaPear Pricing

Plans	Details
Free Trial	3-day free trial, 10 credits included
Paid	Usage-based, no monthly minimums
Best for	Teams that want B2B outcomes without LinkedIn liability

3. PhantomBuster

PhantomBuster is still alive in 2026 and still doing what PhantomBuster has always done: cloud automation for growth workflows, including LinkedIn scraping.

The product has matured a bit, but my opinion has not changed much. It is useful if you want automation. It is much less compelling if you want a clean, durable data infrastructure layer.

PhantomBuster's own pricing page now starts at $59/month with a 14-day free trial, which is a small but meaningful update from the older pricing in the imported article.

The catch remains the same. If you scrape private LinkedIn data through your own account, you are carrying the account risk yourself.

PhantomBuster Pros

• Good for repetitive growth workflows.
• Large library of prebuilt automations.
• Still one of the easiest ways for non-developers to get started.

PhantomBuster Cons

• Still easier to abuse than to operationalize well.
• UI can feel like a toolbox exploded.
• Account safety depends heavily on how aggressive you are.
• Better for automation than for clean downstream data architecture.

PhantomBuster Pricing

Plans	Details
Free Trial	14 days
Basic Paid	$59/mo
High-end Paid	Up to $399+/mo depending on plan

4. People Data Labs

People Data Labs is still a major player for teams that want an enrichment database, not a scraper they operate themselves.

That distinction is why some companies love PDL and others bounce off it immediately.

If your use case is batch enrichment, scoring, analytics, or appending data to an existing system, PDL still makes sense. If your use case is "I need this exact profile to be fresh right now," it gets less exciting.

Their publicly listed person pricing still starts at $98/month, which aligns with the original article.

People Data Labs Pros

• Large structured datasets.
• Good API ergonomics for enrichment workflows.
• Better fit for products than for scrappy manual prospecting.

People Data Labs Cons

• Freshness is the obvious caveat.
• Gets expensive at volume.
• Not the fastest path if your team needs one-off operator workflows.

People Data Labs Pricing

Plans	Details
Free	Up to 100 records
Basic Paid	$98/mo
High-end Paid	Custom pricing

5. ZoomInfo

ZoomInfo is still ZoomInfo. Huge dataset. Expensive. Sales-led. Not built for people who enjoy transparent pricing.

If you buy ZoomInfo, you are not buying a scraper. You are buying a full go-to-market data layer with all the usual pros and pains that come with it.

I still would not recommend it to a developer looking for a flexible LinkedIn scraping substitute. I would recommend it to a large revenue team that wants an all-in-one vendor and has budget.

ZoomInfo Pros

• Huge contact and company database.
• Strong integrations and intent features.
• Mature enterprise workflows.

ZoomInfo Cons

• Pricing opacity remains annoying.
• Overkill for many startups.
• Not API-first in the way technical teams usually want.

ZoomInfo Pricing

Their pricing is still not public. The older reference point of ~$14,995/year as a starting number is still directionally useful, but treat it as a market estimate, not a quoted list price.

6. LinkedIn Sales Navigator API

Like I said in the original article, LinkedIn has its own paid API options. And like I said then, the problem is not whether it exists. The problem is getting and keeping access.

That remains true in 2026.

You still have approvals, restrictions, product-fit questions, and enough administrative friction to make smaller teams reach for third-party tools immediately.

LinkedIn Sales Navigator API Pros

• Official channel.
• Real-time access for approved use cases.
• Strong search/filter capabilities.

LinkedIn Sales Navigator API Cons

• Hard to access.
• Approval process is still the real bottleneck.
• Not built for every use case people imagine.

LinkedIn Sales Navigator API Pricing

Pricing is still not transparently published for API access. The common public benchmark remains the Sales Navigator seat itself at ~$99+/user/month, but actual API access is a separate conversation.

7. Zopto

Zopto is still alive and still very much an outreach-first product that happens to sit on top of LinkedIn workflows.

If you want to automate outbound sequences tied to LinkedIn activity, Zopto can still do the job. If you want deep enrichment or clean data extraction, this is not where I would start.

Zopto Pros

• Works well for LinkedIn outreach sequences.
• Sales Navigator compatibility helps.
• Useful for teams that want campaign orchestration more than data plumbing.

Zopto Cons

• Expensive for smaller teams.
• You are still playing inside LinkedIn's anti-automation blast radius.
• Not a true data platform.

Zopto Pricing

Plans	Details
Free	No free trial
Basic Paid	$197/user/mo
High-end Paid	$237/user/mo

Open-source LinkedIn scrapers

If you are a developer, this category is still tempting.

I get it. Free is seductive.

But "free" in LinkedIn scraping usually means you pay in one of three currencies:

• maintenance time
• account risk
• broken weekends

When I was running FluxoMetric, I burned ~40 hours on one scraping setup that looked cheap on day one and became incredibly expensive by week three. That lesson has held up annoyingly well.

8. linkedin_scraper by joeyism

This project is still the most recognizable open-source LinkedIn scraper in the Python ecosystem.

The core value proposition remains exactly what it was: make profile scraping with Python less painful.

It is still useful for developers who want to tinker, learn, or build a narrow workflow. It is still a bad idea if you think open source means zero operational burden.

linkedin_scraper Pros

• Free.
• Familiar Python workflow.
• Good starting point for developers who want control.

linkedin_scraper Cons

• Continuous maintenance burden.
• Fragile against DOM changes.
• Operational risk is still yours.

9. linkedin-api by tomquirk

This one is still popular because developers love getting clean JSON without manually parsing the front-end.

That part is genuinely nice.

The tradeoff is also unchanged: it requires LinkedIn credentials, which means the risk surface is pretty obvious.

linkedin-api Pros

• Clean JSON output.
• Better developer experience than raw scraping.

linkedin-api Cons

• Requires LinkedIn credentials.
• Account suspension risk is real.
• Bound by whatever LinkedIn changes upstream.

10. LinkScrape by rosstripi

LinkScrape is still a narrower project and mostly useful for company-based employee enumeration.

I still think the original write-up had the right instinct here: the focus is useful, but the narrowness limits it.

LinkScrape Pros

• Good for targeted company scraping.
• Useful if employee enumeration is your exact use case.

LinkScrape Cons

• Narrow scope.
• Session handling is weaker than more mature tools.
• Smaller community means slower troubleshooting.

11. linkedin-scraper by TufayelLUS

This remains one of the more detailed profile-oriented open-source options, especially if you care about skills and endorsements.

That makes it interesting for recruiting experiments and talent analysis. It does not change the maintenance burden.

linkedin-scraper Pros

• More detailed profile extraction than some narrower repos.
• Can handle profiles, jobs, and companies.

linkedin-scraper Cons

• Cookie/session dependence is fragile.
• Smaller community.
• No built-in scale infrastructure.

Browser extension LinkedIn scrapers

This category is still the easiest place for solo operators to get started and the easiest place to make a mess.

Extensions feel safe because they are visible. That is mostly emotional. Not technical.

12. Evaboot

Evaboot is still active in 2026 and still tightly tied to Sales Navigator export workflows.

Its pricing is now very clearly credit-based, and the low-end entry point is still attractive. The official pricing page shows credits starting from $9.

If you already live in Sales Navigator and mainly want cleaner exports plus email enrichment, Evaboot still makes sense.

Evaboot Pros

• Clear use case.
• Easy to understand.
• Good documentation.

Evaboot Cons

• Requires Sales Navigator.
• Credit math can become annoying at scale.
• Limited beyond export and enrichment.

Evaboot Pricing

Plans	Details
Free	No full free plan, low-entry credit purchases
Basic Paid	Starts at $9
Higher Usage	Credit-based, scales with volume

13. MeetAlfred

MeetAlfred still leans more toward omnichannel outreach than true scraping.

That was true before, and it is still true now.

If you want campaigns, sequences, and multichannel activity, it can work. If you want a data extraction product first, I would look elsewhere.

MeetAlfred Pros

• Simple UI.
• Multiple search and outreach workflows.

MeetAlfred Cons

• More outreach tool than scraper.
• Export is not really the center of gravity.

MeetAlfred Pricing

Plans	Details
Free	14-day free trial
Basic Paid	$59/user/mo
High-end Paid	$99/user/mo

14. Octopus CRM

Octopus CRM is still one of the cheaper options in the category and still feels like an automation extension first, scraper second.

That is not a criticism. It is just the product reality.

Octopus CRM Pros

• Cheap.
• Easy enough for non-technical users.
• Good if your main goal is lightweight LinkedIn automation.

Octopus CRM Cons

• Data depth is limited.
• More about workflow automation than high-quality extraction.

Octopus CRM Pricing

Plans	Details
Free	7-day free trial
Basic Paid	$9.99/mo
High-end Paid	$39.99/mo

15. Waalaxy

Waalaxy is still active and the pricing has changed quite a bit from the older imported version. The current pricing page shows entry plans around $16/month, then $32 and $55 tiers depending on the feature set and billing cycle.

My actual opinion on Waalaxy has not changed much. It is approachable. It is also pretty light on real data extraction depth.

Waalaxy Pros

• Beginner-friendly.
• Cheap entry point.
• Good for lightweight outreach workflows.

Waalaxy Cons

• Data richness is limited.
• Better for messaging than for durable enrichment.

Waalaxy Pricing

Plans	Details
Free	Trial/free entry exists
Basic Paid	~$16/mo
Mid-tier	~$32/mo
High-end Paid	~$55/mo

16. Dux-Soup

Dux-Soup is still very much alive. Pricing still starts around $14.99/month, with annual pricing taking it lower.

It is still a sensible choice if you want simple LinkedIn automation without getting buried under a more complex product.

Dux-Soup Pros

• Affordable.
• Onboarding is decent.
• Mature enough that the product does not feel experimental.

Dux-Soup Cons

• Browser dependency is still a pain.
• LinkedIn account risk still exists, regardless of marketing copy.
• More outreach than data platform.

Dux-Soup Pricing

Plans	Details
Free	14-day free trial
Basic Paid	$14.99/mo
Higher Tiers	~$55 to $99/mo

Lead generation and email discovery tools

By this point, it should be obvious that a lot of "LinkedIn scrapers" are really contact data vendors or outbound tools wearing a LinkedIn-shaped hat.

That is not necessarily bad. It just means you should buy the thing for what it actually does.

17. Hunter.io

Hunter.io is still not a LinkedIn scraper in the pure sense. It is an email finding and verification tool.

Still useful. Still better for domain-based contact discovery than for LinkedIn-specific extraction.

Hunter.io Pros

• Simple and reliable.
• Good email verification.

Hunter.io Cons

• Not a true LinkedIn data tool.
• False positives still happen.

Hunter.io Pricing

Plans	Details
Free	Free plan available
Basic Paid	$34/mo
High-end Paid	$349/mo

18. Lusha

Lusha is still alive and still popular with sales teams that want extension + API flexibility.

I still hear the same split feedback I heard years ago: people like the convenience, and they complain when the data is wrong.

That is not unique to Lusha. It is just the reality of B2B contact data.

Lusha Pros

• Easy to use.
• Good CRM integrations.
• Useful extension workflow.

Lusha Cons

• Accuracy complaints still come up.
• Not really built for raw scraping use cases.

Lusha Pricing

Plans	Details
Free	50 emails / 5 phone numbers
Basic Paid	$49/user/mo
High-end Paid	Custom

19. Apollo.io

Apollo is still one of the most commercially useful tools on this entire list, but calling it a LinkedIn scraper is still slightly misleading.

It is a sales engagement and contact database platform. It just overlaps heavily with the same jobs people once tried to solve by scraping LinkedIn manually.

Apollo.io Pros

• Rich workflow automation.
• Strong search filters.
• Good for SDR and outbound teams.

Apollo.io Cons

• Data quality is uneven in places.
• Gets expensive when you scale seats and usage.
• Can encourage a lot of mediocre automation if your team is sloppy.

Apollo.io Pricing

Plans	Details
Free	1,200 credits/year
Basic Paid	$59/user/mo
High-end Paid	$149/user/mo

20. UpLead

UpLead still appeals to teams that want verified contact data and are willing to trade some volume for cleaner records.

That is still the right way to think about it.

UpLead Pros

• Verification-first model is useful.
• Good for teams that hate wasting credits on junk.

UpLead Cons

• Lower volume than some competitors.
• Price-to-database-size tradeoff can feel rough.

UpLead Pricing

Plans	Details
Free	7-day trial, 5 credits
Basic Paid	$99/mo
High-end Paid	Custom

21. Lemlist

Lemlist remains more of an outreach platform than a LinkedIn scraping tool.

It is still useful, but you should not buy it expecting it to solve data acquisition at the source.

Lemlist Pros

• Strong sequencing and personalization.
• Good multichannel workflows.

Lemlist Cons

• Mixed customer support feedback remains.
• Not a core scraping product.

Lemlist Pricing

Plans	Details
Free	14-day free trial
Basic Paid	$39/user/mo
High-end Paid	$159/user/mo

22. Snov.io

Snov.io still sits in that hybrid bucket of lead generation, outreach, and small CRM functionality.

The original complaint in the imported piece still stands, honestly. For a tool people often mention in LinkedIn workflows, the LinkedIn-native value is not as strong as you might expect.

Snov.io Pros

• Easy onboarding.
• Good for all-in-one lightweight outbound.

Snov.io Cons

• Not a strong pure LinkedIn extraction product.
• Refund policy is still a turnoff for some buyers.

Snov.io Pricing

Plans	Details
Free	50 credits
Basic Paid	$39/mo
High-end Paid	Custom

Data aggregation and analytics vendors

This is the category people under-appreciate when they obsess over scraping tools.

If your job is analytics, market mapping, workforce intelligence, or research, you often do not want a scraper. You want a vendor that already did the collection and structuring.

23. Revelio Labs

Revelio Labs is still a serious workforce intelligence platform. Still expensive. Still not for casual users.

The older estimate of ~$85,000/year is still best treated as directional, because public pricing remains unavailable.

Revelio Labs Pros

• Serious workforce analytics.
• Good for benchmarking and labor-market intelligence.

Revelio Labs Cons

• Price opacity.
• Narrower B2B use case than general enrichment vendors.

24. Xverum

Xverum is still around, still relatively opaque, and still not nearly as transparent as I would like for a buyer trying to compare options.

Xverum Pros

• API-oriented access.
• Broad firmographic and profile-style data coverage.

Xverum Cons

• Weak pricing transparency.
• Harder to validate freshness and user satisfaction.

25. Coresignal

Coresignal is still active and the official docs still show API subscriptions from $49/month, with full datasets starting around $1,000.

This remains one of the more credible options if you want structured datasets and are comfortable with the usual freshness tradeoffs.

Coresignal Pros

• Useful formats and delivery methods.
• Good for teams that want datasets or search APIs.

Coresignal Cons

• Freshness complaints still matter.
• "Real-time" can be slower than buyers expect.

Coresignal Pricing

Plans	Details
Free	Trial credits available
Basic Paid	$49/mo
High-end Paid	$1,500/mo
Datasets	From ~$1,000

26. TalentNeuron

TalentNeuron is still workforce analytics software first, LinkedIn-adjacent data tool second.

If you are doing hiring strategy, geography analysis, and labor market planning, it can be useful. If you are trying to build outbound lists, it is the wrong category.

TalentNeuron Pros

• Good for strategic workforce planning.
• Combines multiple data sources.

TalentNeuron Cons

• Weak self-serve accessibility.
• Not built for flexible downloads the way many buyers want.

27. SeekOut

SeekOut is still strong for recruiting, especially in North America.

I still would not stretch it into use cases it is not built for.

SeekOut Pros

• Strong recruiting filters.
• Good search experience.

SeekOut Cons

• Narrower geography and use case focus.
• Less useful outside recruiting.

SeekOut Pricing

Public pricing is still not clearly listed. Market references still put plans starting around $499/month.

28. Entelo

Entelo remains in the predictive recruiting bucket. Useful in that lane. Not particularly compelling outside it.

Entelo Pros

• Predictive hiring workflows.
• ATS-friendly.

Entelo Cons

• Limited scale and flexibility versus broader data platforms.

No-code LinkedIn scrapers

These are for the people who want extraction without writing code.

That is a valid need. It is also where buyers sometimes confuse "easy setup" with "good long-term decision".

29. Octoparse

Octoparse is still alive and the current pricing page shows $69/month for Standard and $249/month for Professional, with a free plan.

The original article liked the point-and-click interface. I still do too. But LinkedIn remains one of the harder places for these generic no-code scrapers to work reliably.

Octoparse Pros

• Good no-code UX.
• Multi-purpose beyond LinkedIn.
• Free tier is useful for testing.

Octoparse Cons

• Generic scraper limitations show up fast on LinkedIn.
• Dynamic page handling is still where things get annoying.

Octoparse Pricing

Plans	Details
Free	10 tasks
Basic Paid	$69/mo
High-end Paid	$249/mo

30. Bright Data

Bright Data is still more infrastructure than turnkey LinkedIn scraping solution.

That is why technical teams like it and non-technical buyers often get frustrated.

If you want proxies, scraping infrastructure, and dataset options, it is still one of the strongest vendors around. If you want "just give me leads," this is too much machinery.

Bright Data Pros

• Strong proxy network.
• Serious scraping infrastructure.
• Useful if you are building your own stack.

Bright Data Cons

• Complex setup.
• Can get expensive fast.
• Better for operators than for regular sales teams.

Bright Data Pricing

The older article's point still stands: pricing is complicated and highly segmented. Expect starting points in the ~$500/month range for meaningful infrastructure usage.

31. ParseHub

ParseHub is still one of the more approachable no-code tools, and I still think the point-and-click interface is its best feature.

I would still not choose it as my first LinkedIn-specific option because LinkedIn's defenses make generic scrapers flaky here.

ParseHub Pros

• Friendly interface.
• Good for general web extraction tasks.

ParseHub Cons

• LinkedIn anti-bot measures are still a problem.
• Troubleshooting failed projects can get tedious.

ParseHub Pricing

Plans	Details
Free	200 pages per run window
Basic Paid	$189/mo
High-end Paid	Custom

32. Import.io

Import.io is still a no-code-to-semi-technical extraction platform rather than a LinkedIn-specialist tool.

The imported article was right to note that pricing is still annoyingly opaque.

Import.io Pros

• Flexible.
• Good for scheduled extraction and downstream integrations.

Import.io Cons

• Not LinkedIn-specific.
• Manual intervention is still common for difficult pages.

+1. iScraper, dead and worth remembering

iScraper is the "+1" because dead tools teach more than live ones sometimes.

2026 update: iScraper is dead. LinkedIn sued it.

I am including it because too many roundup articles quietly delete failed operators and then pretend the risk was theoretical all along. It was not.

If you are building a company that depends on LinkedIn-derived data, the right question is not just "does this tool work today?" The right question is also:

• what happens if LinkedIn notices?
• what happens if they sue?
• what happens to my customers, my data, and my code if this blows up?

iScraper is what happens when those questions stop being abstract.

iScraper Pros

• Historically, it solved a real demand.

iScraper Cons

• Dead.
• Sued by LinkedIn.
• Perfect example of why "working" and "durable" are not the same thing.

Comparison table

Because this article compares more than three tools, here is the table I wish more people started with.

Tool	Best for	Data Quality	Pricing	Ease of Use	API / Integration	Durability	Avg. Score
NinjaPear	Competitive intel without LinkedIn risk	⭐⭐⭐⭐☆	⭐⭐⭐⭐☆	⭐⭐⭐⭐☆	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐	4.40/5
PhantomBuster	Automation workflows	⭐⭐⭐☆☆	⭐⭐⭐☆☆	⭐⭐⭐⭐☆	⭐⭐⭐☆☆	⭐⭐☆☆☆	3.00/5
People Data Labs	Enrichment/database	⭐⭐⭐⭐☆	⭐⭐☆☆☆	⭐⭐⭐☆☆	⭐⭐⭐⭐⭐	⭐⭐⭐☆☆	3.40/5
Evaboot	Sales Nav export	⭐⭐⭐☆☆	⭐⭐⭐⭐☆	⭐⭐⭐⭐⭐	⭐⭐☆☆☆	⭐⭐☆☆☆	3.20/5
Coresignal	Datasets/API	⭐⭐⭐⭐☆	⭐⭐⭐⭐☆	⭐⭐⭐☆☆	⭐⭐⭐⭐☆	⭐⭐⭐☆☆	3.60/5
Octoparse	No-code scraping	⭐⭐☆☆☆	⭐⭐⭐☆☆	⭐⭐⭐⭐☆	⭐⭐☆☆☆	⭐⭐☆☆☆	2.60/5
Dux-Soup	Simple LinkedIn automation	⭐⭐☆☆☆	⭐⭐⭐⭐☆	⭐⭐⭐⭐☆	⭐⭐☆☆☆	⭐⭐☆☆☆	2.80/5
Apollo.io	Sales engagement + contact data	⭐⭐⭐⭐☆	⭐⭐⭐☆☆	⭐⭐⭐⭐☆	⭐⭐⭐⭐☆	⭐⭐⭐☆☆	3.60/5

My blunt take:

• If you want LinkedIn automation, PhantomBuster or Dux-Soup are still serviceable.
• If you want LinkedIn export from Sales Navigator, Evaboot is still one of the cleaner options.
• If you want database/API enrichment, People Data Labs and Coresignal are the more relevant comparisons.
• If you want the business outcome without LinkedIn liability, NinjaPear is the more interesting product category.

How do I find the best LinkedIn scraper for me?

30+ options is too many unless you simplify the decision.

Here is the only framework I would use now.

Technical proficiency

If you are a developer, you can still make open-source tools work. The question is whether you should.

If you're non-technical, browser extensions and no-code tools will get you to first output faster. They will not necessarily get you to a durable workflow.

Data depth and freshness

This is still the most under-rated filter.

Ask these questions:

• Is the data fetched on demand or from a prebuilt database?
• Can I control freshness?
• What fields actually come back?
• What happens when the source changes?

A lot of buyers compare shiny landing pages and never ask the questions that matter.

Purpose

This is where most people screw up.

If your real goal is outreach, buy an outreach product. If your real goal is enrichment, buy an enrichment API. If your real goal is competitive intel, buy a competitive intel platform.

Do not buy a Chrome extension and expect it to become a data moat.

Budget

Open source is cheapest in cash and most expensive in founder attention.

Enterprise data vendors are expensive in cash and often cheap in internal engineering time.

The wrong middle ground is paying a modest monthly fee for a tool that creates hidden downstream chaos.

I've done that. It feels cheap. It is not cheap.

Ease of use

Waalaxy, Evaboot, and ParseHub are easy to get started with.

That matters. But ease of use on day one is not the same as ease of operating at month six.

Scalability

If this is becoming part of a real workflow, think about:

• API access
• export formats
• CRM sync
• rate limits
• whether your workflow depends on a human browser session being open

That last one sounds stupid until it breaks a pipeline you thought was automated.

Is LinkedIn scraping legal?

Here is the narrow answer first.

Public scraping is not automatically criminal after hiQ.

Here is the useful operator answer.

That does not mean building a business on LinkedIn-derived data is safe.

I want to be very precise here because people love flattening this into internet-lawyer sludge.

The best recent write-up on this is the Nubela post Is Scraping LinkedIn Legal in 2026? (I Was Sued by LinkedIn). The sentence that matters most is this one:

public scraping may be outside one narrow theory of criminal or statutory liability, but that does not make your company safe from LinkedIn.

That is the whole thing.

The original version of this article was too casual about legal risk. That was a mistake.

What matters in 2026 is not just whether a court says public scraping is automatically criminal. What matters is:

• LinkedIn's Terms of Service
• breach-of-contract exposure
• civil claims
• customer notification risk
• data deletion risk
• derivative-data deletion risk
• discovery hell

That last one sounds abstract until you have to deal with it.

That Reddit comment gets one thing exactly right: legal and safe are not synonyms.

A few practical liability notes:

• If your employees use LinkedIn accounts, you may already be in contract land.
• Buying LinkedIn-derived data from a broker does not magically clean the chain of custody.
• If a plaintiff asks for deletion of inferred or downstream data, the blast radius gets ugly fast.
• If your entire GTM stack depends on LinkedIn-derived workflows, diligence during an acquisition will get uncomfortable.

So, is LinkedIn scraping legal?

Narrow legal answer: sometimes public scraping may be defensible.

Business answer: I would not call it durable.

My recommendation

I have two recommendations now, not one.

If you still want a LinkedIn scraper

Pick based on your actual job:

• PhantomBuster for flexible automation.
• Evaboot for Sales Navigator export.
• People Data Labs or Coresignal for API/database workflows.

That is the cleanest version of the old recommendation set.

If you want the commercial outcome without the LinkedIn liability

Use NinjaPear.

This is the part I feel strongest about in 2026.

Most teams do not actually need LinkedIn scraping. They need:

• better prospecting inputs
• fresher account signals
• customer and competitor mapping
• person and company enrichment
• work emails
• a reason to reach out now, not six weeks from now

NinjaPear gives you that without building on LinkedIn data.

That matters more than people think.

When I was running FluxoMetric, I burned ~4K/month on tools that gave me worse signal than a decent analyst with a browser and patience. The issue was never lack of data. It was that the data was blurry, stale, or legally awkward. NinjaPear is much closer to what I wish I had back then: a direct path to competitive intelligence and prospecting signal, not a fragile dance around someone else's platform rules.

Final thoughts

The original article had the right instinct: there are a lot of options, and they are not interchangeable.

The 2026 update is simpler.

LinkedIn scrapers still exist. Several are still useful. But the category has aged badly if you care about business durability.

That is the update.

If you still need a LinkedIn scraper, use the table above and buy the narrowest tool that matches your use case.

If you are tired of building GTM workflows on top of legal gray zones, Chrome extensions, and somebody else's tolerance threshold, try NinjaPear instead. Start with the free trial, test a few real accounts, and see if you can get the outcome you wanted from LinkedIn without touching LinkedIn at all.

FAQs

Is it possible to scrape data from LinkedIn?

Yes. Technically, it is still very possible. That has never been the hard part.

What is the safest LinkedIn scraper?

There is no magic safe scraper. There are only different tradeoffs between convenience, account risk, legal exposure, and durability.

Which LinkedIn scraper is best for developers?

Historically, Proxycurl was the strongest API-first answer, but it has been sunset. In 2026, developers should separate the problem into two parts: if you truly need LinkedIn scraping, use a specialized live vendor. If you need B2B intelligence outcomes, use NinjaPear instead.

Is Proxycurl still available?

No. Proxycurl API has been sunset.

What replaced Proxycurl?

The founder behind Proxycurl is now building NinjaPear, but NinjaPear is not a LinkedIn scraper replacement in the literal sense. It is a better answer for teams that want B2B data, prospecting, and competitive intelligence without depending on LinkedIn-derived data.

What happened to iScraper?

It is dead and was sued by LinkedIn.

Can I avoid LinkedIn scraping entirely?

Yes, and for more teams than you think, you probably should. If your real need is customer intel, competitor monitoring, company enrichment, employee search, or work email lookup, a non-LinkedIn platform like NinjaPear can get you there with a lot less baggage.