If you built anything on Proxycurl's LinkedIn Profile API, July 2025 was a rough month. LinkedIn's lawsuit forced them to shut down, leaving ~200K customers scrambling for alternatives. Your enrichment pipeline broke, your sales team lost real-time prospect data, and your recruiting tools went dark overnight.
I've spent the last few weeks testing every replacement I could find. Here's what actually works in 2026.
Who Needs LinkedIn Profile Data (And Why It Matters)
LinkedIn profile scraping isn't just a developer curiosity — it powers serious business workflows:
- Sales teams enrich CRM leads with job titles, company names, and career history to personalize outreach
- Recruiters pull candidate profiles at scale to build talent pipelines without manual copy-paste
- Marketers build Ideal Customer Profiles (ICPs) by analyzing the demographics of existing customers
- Researchers study labor market trends, skill demand shifts, and workforce mobility
Proxycurl gave all of these teams a clean REST API: send a LinkedIn URL, get back structured JSON with name, title, company, education, experience, skills, and more. Simple, fast, reliable — until it wasn't.
The 5 Best Alternatives in 2026
1. Apify LinkedIn Profile Scraper
Best for: Developers who want full control and pay-per-result pricing.
Apify runs actors (serverless scrapers) in the cloud. The LinkedIn Profile Scraper accepts a list of profile URLs and returns structured JSON with all the fields Proxycurl offered — name, headline, current position, experience history, education, skills, and location.
- Pricing: Pay-per-event (~$0.035/profile on the Apify platform)
- Fields: Full profile — name, headline, experience, education, skills, location, connections count
- Rate limits: Controlled by your Apify plan (scales to thousands of profiles/day)
- Legal stance: Runs on Apify's infrastructure; you control usage
2. Scrapingdog LinkedIn Scraper API
Best for: Teams that want a drop-in REST API with a free tier to test.
Scrapingdog offers a dedicated LinkedIn endpoint that returns profile data as JSON. Their free plan includes 1,000 credits — enough to validate your pipeline before committing.
- Pricing: Free tier (1,000 credits), then from $40/mo
- Fields: Name, headline, experience, education, location, about section
- Rate limits: Based on plan tier
- Legal stance: Proxy-based; they handle rotation and anti-bot
3. LinkdAPI
Best for: Event-driven architectures that need webhook delivery.
LinkdAPI differentiates with async webhook support — submit a profile URL, get results POSTed to your endpoint when ready. Useful if you're enriching leads in a queue-based system.
- Pricing: From $49/mo for 500 profiles
- Fields: Name, title, company, experience, education, certifications
- Rate limits: 500-10,000 profiles/mo depending on plan
- Legal stance: Operates as a data provider; ToS compliance is user's responsibility
4. Bright Data LinkedIn Dataset
Best for: Bulk analysis where you need thousands of profiles at once.
Bright Data offers pre-collected LinkedIn datasets and on-demand collection. Less "API" and more "data pipeline" — you define your target criteria, they deliver a dataset.
- Pricing: Custom pricing; typically $0.01-0.05/record for bulk
- Fields: Comprehensive — full profile, company data, skills endorsements
- Rate limits: N/A (batch delivery)
- Legal stance: They position themselves as compliant under data protection frameworks
5. PhantomBuster LinkedIn Profile Scraper
Best for: Non-technical teams that want a no-code solution.
PhantomBuster provides browser-based "Phantoms" that scrape LinkedIn using your own session cookie. It's the most accessible option for sales teams without developer support.
- Pricing: From $69/mo for 500 automations
- Fields: Name, headline, experience, education, connections
- Rate limits: ~80 profiles/day to avoid LinkedIn detection
- Legal stance: Uses your own LinkedIn session — risk is on you
Comparison Table
| Feature | Apify | Scrapingdog | LinkdAPI | Bright Data | PhantomBuster |
|---|---|---|---|---|---|
| Free tier | Trial credits | 1,000 free credits | No | No | 14-day trial |
| Per-profile cost | ~$0.035 | ~$0.04 | ~$0.10 | ~$0.01-0.05 | ~$0.14 |
| Webhook support | Via integration | No | Yes (native) | No | Zapier |
| Full experience history | Yes | Yes | Yes | Yes | Yes |
| Skills & endorsements | Yes | Partial | Yes | Yes | No |
| Batch processing | Yes (built-in) | Sequential | Async queue | Native batch | Sequential |
| Self-hosted option | Yes (open source) | No | No | No | No |
Migration Guide: Proxycurl to Apify in 10 Minutes
If you had Proxycurl code like this:
import requests
# Old Proxycurl code (no longer works)
resp = requests.get(
"https://nubela.co/proxycurl/api/v2/linkedin",
params={"url": "https://linkedin.com/in/williamhgates"},
headers={"Authorization": "Bearer YOUR_PROXYCURL_KEY"}
)
profile = resp.json()
print(profile["full_name"], profile["headline"])
Here's the Apify equivalent:
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("cryptosignals/linkedin-profile-scraper").call(
run_input={
"profileUrls": ["https://linkedin.com/in/williamhgates"]
}
)
for profile in client.dataset(run["defaultDatasetId"]).iterate_items():
print(profile["name"], profile["headline"])
print(f"Current: {profile.get('currentCompany', 'N/A')}")
print(f"Experience: {len(profile.get('experience', []))} positions")
print(f"Skills: {', '.join(profile.get('skills', [])[:5])}")
The key differences:
- Async by default — Apify runs the scrape as a job, so you get richer data but wait a few seconds
- Batch-native — pass 100 URLs in one call instead of looping
- Dataset storage — results are stored and queryable, not just returned once
Install the client with pip install apify-client and grab your API token from Apify Console.
Which One Should You Pick?
- Need a quick REST API with free testing? Start with Scrapingdog — their free tier lets you validate without a credit card.
- Building a production enrichment pipeline? Go with Apify — pay-per-result scales better than monthly subscriptions, and the actor model lets you customize extraction.
- Processing webhooks in an event-driven system? LinkdAPI is purpose-built for this.
- Need 50K+ profiles for analysis? Bright Data bulk datasets are the most cost-effective at scale.
- Non-technical team? PhantomBuster gets you started without writing code.
The Proxycurl shutdown was painful, but the ecosystem has matured. You actually have better options now than you did in 2024 — more flexible pricing, better batch support, and open-source alternatives you can self-host.
Building a LinkedIn data pipeline? I maintain the LinkedIn Profile Scraper on Apify — it's optimized for reliability and returns the same structured fields Proxycurl did.
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