TL;DR
Proxycurl by Nubela — the LinkedIn-focused enrichment API — has had a turbulent 2024–2026 after LinkedIn's enforcement push and the related lawsuits. If you're searching "Proxycurl status 2026" or "nubela proxycurl status 2026," you're probably trying to figure out whether to renew, switch, or build your own data pipeline. For most teams, the answer in 2026 is: don't rebuild your stack around a single LinkedIn-data API. Instead, run a free, browser-based scraper like ScrapeMaster on the public pages you actually need, in your own browser session, with no API key risk.
A short timeline of Proxycurl and its problems
Proxycurl was, for years, the leading "LinkedIn API substitute" — a paid service that returned structured profile and company data on demand. Lots of recruiting, sales, and venture-capital tools quietly used it under the hood.
Then a few things happened:
- 2023: hiQ Labs vs LinkedIn finally concluded after years of remand — a partial settlement that left the legal landscape muddier than it started.
- 2024: LinkedIn intensified TOS enforcement and pushed user-agreement language that more explicitly prohibits automated access by third parties.
- Late 2024 / 2025: Nubela's founder publicly described being sued by LinkedIn, with the company's posture and pricing shifting throughout the year.
- 2026: searches for "Proxycurl shutdown" and "Proxycurl status 2026" spike — a signal that many customers can no longer count on uninterrupted service.
The result: even if Proxycurl is technically operating in May 2026, building a business on top of a single LinkedIn-data vendor is now a fragile architecture. Every quarter brings new uncertainty about what data is allowed, how it's allowed to be obtained, and whether the vendor will still be in business in twelve months.
What "Proxycurl status 2026" really means in practice
If you're a current Proxycurl customer:
- API uptime varies. Several customers in 2025–2026 have reported intermittent endpoint deprecations as Nubela responds to LinkedIn enforcement.
- Coverage is narrower than it used to be — specific profile fields have come and gone.
- Pricing has shifted from "all-you-can-eat tiered" toward credit-based metering.
- Legal exposure is borne ultimately by you, the buyer — if your downstream product is built on data that's later deemed obtained in violation of LinkedIn's TOS, that's your problem too.
If you're a prospective customer:
- The risk is even higher. You're being asked to build a roadmap and integration around a vendor whose own roadmap is contingent on litigation outcomes.
- Cheaper, simpler, browser-based alternatives may give you 80% of what you needed without any API dependency.
Why browser-based scraping is the cleaner architecture in 2026
The core idea: instead of paying an API to do automated access at scale on your behalf, you (the human) browse LinkedIn the normal way, and a Chrome extension structures what's on your screen as you go.
ScrapeMaster is built for this:
- No bot signature — the activity is you, logged into your LinkedIn, scrolling the way you'd scroll anyway.
- No API key that can be deactivated overnight by a vendor change.
- No vendor in the middle — the data your tool collects comes from pages you're already viewing.
- No upload to external servers — extraction runs in the extension, output goes to CSV/Excel/JSON on your machine.
- No subscription — the extension is free.
This is a different legal posture from Proxycurl. You are an authenticated, human user accessing LinkedIn within your own session. You are bound by LinkedIn's user agreement, but you're not running a server-side scraper in violation of automated access prohibitions. Many teams find this position much more defensible.
Important: read LinkedIn's user agreement and use whatever data you collect responsibly. Public profile information has different legal status from private connection lists. The HiQ remand, the Bright Data cases, and ongoing 2026 litigation (Reddit v. Perplexity, the YouTube creator class actions vs. Snap and Meta) are all live ground for re-interpretation. Don't take blanket "scraping is fine" or "scraping is always illegal" advice from anyone on the internet — including this post.
Proxycurl vs ScrapeMaster (and other 2026 options)
| Tool | Architecture | LinkedIn-specific | Bot signature | Free tier | Vendor risk |
|---|---|---|---|---|---|
| Proxycurl (Nubela) | Server-side API | Yes | Yes (server traffic) | No | High (litigation) |
| Phantombuster | Cloud automation | Yes | Yes | Limited | Medium-high |
| LinkedIn Sales Navigator API | Official | Yes | Authorized | No (paid Sales Nav) | Low |
| Apollo.io | Aggregated DB | Yes (cached) | N/A | Limited | Medium (data freshness) |
| ScrapeMaster | In-browser extension | No (general purpose) | None (you're the user) | Yes | None |
| Manual copy/paste | Manual | Universal | None | Yes | None (just slow) |
ScrapeMaster won't replace Proxycurl for automated enrichment at scale. It will replace Proxycurl for building a focused list of accounts/profiles you actually intend to engage with, which is what most teams need 80% of the time.
A practical 2026 stack for LinkedIn-adjacent workflows
Here's a stack that holds up across recruiting, sales prospecting, and competitive research:
1. Your own session for collection
- LinkedIn open in Chrome, logged in as you.
- Search filters tuned for the target persona.
- ScrapeMaster sidebar open, picking up names, titles, current company, and public bio text.
This is the data you're going to act on. It doesn't need to be every profile on LinkedIn. It needs to be the right 200, 500, or 2,000 for your campaign.
2. Local enrichment from open sources
- Personal sites, GitHub, company pages, podcast appearances.
- All scrapeable from Chrome via the same extension.
- All public, no auth required, no LinkedIn TOS implications.
3. CRM ingest
- ScrapeMaster exports to CSV / Google Sheets / JSON.
- Drop into Salesforce, HubSpot, Apollo, your own database.
- Run your existing CRM dedupe rules; the data flow is identical to "manually entered prospect."
4. Archive for compliance
- Use Convert: Web to PDF to save snapshots of the public profile pages you collected from, on the date you collected.
- Important if you ever need to demonstrate that information was public at the time of collection.
This stack has zero API vendor risk, zero "what if Nubela folds" risk, and a defensible "human user with their own browser session" legal posture.
What if you absolutely need scale?
If you're enriching tens of thousands of profiles per month, a browser-based extension isn't the right answer — you need legitimate, contracted data access. The 2026 options:
- LinkedIn Talent Insights / Sales Navigator API — official, paid, authorized. Expensive but bulletproof.
- People Data Labs / Coresignal / Brookfield — large data brokers with their own collection methods and their own legal disclosures. Read carefully.
- Apollo.io / ZoomInfo — aggregated contact databases. Older data than live LinkedIn but generally lower legal risk.
If you don't have a contract relationship with one of these and you're scraping at scale, the legal exposure scales linearly with your volume. The cost of an enterprise data deal often turns out lower than the cost of one lawsuit.
How to migrate off Proxycurl this quarter
If you're a current Proxycurl customer planning an exit:
Week 1 — audit current usage
- How many calls per month?
- Which endpoints (person, company, lookup, search)?
- What fields actually get consumed downstream?
You'll likely find 80% of your API spend goes to fields that aren't materially driving outcomes.
Week 2 — score the use cases
- "I need to enrich a list of 5,000 prospects I bought from a list provider" → migrate to Apollo or PDL
- "I need to know who's hiring at company X right now" → switch to a manual LinkedIn search with ScrapeMaster
- "I need a name and title for every employee at Y company" → switch to LinkedIn Talent Insights, or accept that this data class is no longer reliably purchasable
Week 3 — implement
- New CSV / Sheets ingest paths from ScrapeMaster.
- New API contracts where needed.
- Decommission Proxycurl-specific code paths.
Week 4 — verify
- Are downstream metrics (open rate, reply rate, close rate) stable?
- Are sales reps happier or unhappier? (Manual collection often produces better prospect lists; the worse data was a hidden cost.)
Why the browser-based approach is winning in 2026
A pattern across 2025 and 2026: enforcement-and-litigation pressure on automated-access vendors has steadily reduced their reliability, while in-browser tools have steadily improved.
- No server-side scraping to fingerprint — you're a real user.
- No proxy farm to detect — you're on your own IP, like any other LinkedIn user.
- No anti-bot dance — the activity literally is human-driven; the extension just structures what you see.
Compare to the legal pressure on the server-side ecosystem:
- Reddit v. Perplexity, SerpApi, Oxylabs, AWMProxy (industrial-scale scraping)
- YouTube creator class actions vs. Snap, Meta (DMCA scraping)
- Google v. SerpApi (DMCA circumvention) — hearing on May 19, 2026
- LinkedIn v. Nubela / similar (TOS enforcement)
The browser-based architecture is upstream of all of these. The cases either don't apply, or they apply at a much weaker level because the human-in-the-loop pattern is fundamentally different from industrial scraping.
What ScrapeMaster does well (and where it doesn't fit)
Where ScrapeMaster shines:
- One-click structured extraction from LinkedIn search results, profile lists, company employee pages
- CSV / Excel / Google Sheets / JSON export with consistent column structure
- No coding — point, click, extract
- No paywall — free, browser-based, no account
- Works on any public web page, not just LinkedIn — useful for combining LinkedIn data with company website data, GitHub, podcast pages, etc.
Where ScrapeMaster won't replace a server-side service:
- Round-the-clock unattended scraping (by design — you have to be at the browser)
- Bulk historical backfills of millions of profiles (use a legitimate data vendor)
- API-style integration where another service calls a URL and gets JSON back (no API surface; this is a browser extension)
If your needs are "I want a clean list of the right 1,000 prospects this week," ScrapeMaster + a logged-in browser session beats most paid APIs. If your needs are "I want a real-time stream of every job change at every Fortune 500 company," you need a different category of tool entirely — and probably an enterprise data contract.
A note on AI-driven LinkedIn workflows
Several 2026 startups are pitching "AI agents that scrape LinkedIn for you." These typically run server-side automated browsers on infrastructure they control. From LinkedIn's TOS perspective, the user-agent is still automated, the IPs are still server farms, the access is still bot-like — and most of those vendors will face the same enforcement curve Proxycurl has been on.
A safer 2026 pattern: a human (you) browses LinkedIn, an extension (ScrapeMaster) structures what's on screen, and a separate AI agent (running locally or on your private infra) does whatever reasoning you want on the exported data. The AI never touches LinkedIn directly. Detection surface goes way down.
For research on which AI models to use for that reasoning step, CineMan AI lets you compare current model capabilities side-by-side without uploading anything to a third party.
Frequently asked questions
Q: Is Proxycurl shut down?
As of May 2026, Proxycurl/Nubela continues to operate, but coverage and pricing have shifted in response to LinkedIn enforcement and litigation. Whether the service is "reliable" for a business-critical pipeline depends on your risk tolerance. Many teams have migrated off in 2025–2026.
Q: Is scraping LinkedIn legal?
The legal landscape is unsettled. Public profile data has been the subject of years of litigation (hiQ vs LinkedIn, ongoing). The HiQ remand established that scraping public data isn't categorically illegal under the Computer Fraud and Abuse Act, but it didn't bless scraping in violation of LinkedIn's user agreement. Get your own legal advice before scaling.
Q: Is using a Chrome extension on my own LinkedIn account legal?
You're bound by LinkedIn's user agreement, which prohibits using bots or automation against LinkedIn. A browser extension that structures pages you are viewing is closer to "manual use" than to "automated access," but it's not zero-risk. Read the user agreement and use ScrapeMaster on profiles you have a legitimate reason to view.
Q: Will my LinkedIn account get banned for using ScrapeMaster?
ScrapeMaster doesn't automate logins or hammer endpoints in the background. The activity LinkedIn sees is you, browsing as you would anyway. Compared to running an automated scraper or signing into your account from a server-side bot, the detection surface is dramatically lower.
Q: What about Phantombuster, Apollo, or Cognism?
Each has its own approach. Phantombuster runs cloud automations against LinkedIn under your account (some legal/operational risk); Apollo and Cognism are aggregated databases built from various sources (the data is older but the legal posture is different). Pick based on your use case — none of them is a drop-in Proxycurl replacement.
Q: How does ScrapeMaster compare to Octoparse or ParseHub?
Octoparse and ParseHub are general-purpose scrapers, often desktop apps or cloud workflows. They're powerful but have a learning curve and (for cloud editions) similar legal posture to other server-side approaches. ScrapeMaster is a one-click browser extension — simpler, in-session, faster to start.
Q: Can I export to my CRM directly?
ScrapeMaster exports to CSV and Google Sheets natively. From there, most CRMs (Salesforce, HubSpot, Pipedrive, Close) have CSV/Sheets import. You can also script a Sheets → CRM sync with Zapier or similar.
Q: What about scraping company pages instead of profiles?
Yes — ScrapeMaster works on LinkedIn company pages, employee lists, job postings, and search result pages. The same one-click extraction model applies.
Q: Is there an API I can call from my own code?
ScrapeMaster is browser-based, not API-based. The reason it stays low-risk is that it runs in your session. An API would mean automated server access, which is exactly the architecture LinkedIn pushes back on.
Q: What if I just want to enrich a list of 50,000 contacts?
That scale is closer to data-broker territory. Look at Apollo, ZoomInfo, People Data Labs, or LinkedIn's own Sales Navigator API. ScrapeMaster is optimized for "the right hundreds to thousands," not the millions.
Q: Should I archive the profiles I scrape?
Yes. Use Convert: Web to PDF on each profile you act on. Timestamped PDFs are useful for compliance, for legal defense if a profile changes, and for personal recall later.
Bottom line
"Proxycurl status 2026" is, fundamentally, a question about how much vendor risk you can absorb. The right answer for most teams is: less than you have today.
The browser-based architecture — you logged into LinkedIn, ScrapeMaster capturing what's already on your screen, exports to CSV — is cheaper, simpler, and structurally less exposed to the litigation wave reshaping the automated-access market in 2025–2026.
For most LinkedIn-related workflows in 2026, that's the right place to start.