How to Scrape OnlyFans in 2025: Complete Step-by-Step Guide

Scraping public data from OnlyFans in 2025 isn’t just possible—it can be incredibly useful when done ethically, legally, and with the right tools. Whether you're a researcher, analyst, marketer, or just curious about pricing trends, understanding how to extract public data from OnlyFans can unlock valuable insights.

But this isn’t just about writing a Python script and calling it a day. OnlyFans is a dynamic, JavaScript-heavy platform with evolving authentication methods, rate limits, and bot protection mechanisms. So to do it properly, you’ll need the right mix of browser automation, scraping libraries, and awareness of ethical boundaries.

In this guide, I’ll walk you through everything you need to know about how to scrape OnlyFans in 2025, using browser tools, Python scripts, or specialized APIs. No fluff—just real, working methods for gathering public data responsibly.

Important: This guide is for educational purposes only. Do not use scraping techniques to bypass paywalls, access private content, or violate the rights of creators or platforms. Respect the law, respect the creators.

Why Scrape OnlyFans Data in 2025?

Before we dive into the how, let’s talk about the why. There are legitimate reasons for scraping OnlyFans—if you’re working with public content that you have access to.

Here are some examples:

• Market Research for Creators: Analyze public subscription prices, engagement stats, and bios to understand how other creators position themselves.
• Competitive Intelligence: Agencies and managers may want to study public-facing creator profiles to advise their clients better.
• Academic Research: Researchers studying digital economies, creator monetization models, or platform behavior may need data at scale.
• Pricing & Trend Monitoring: Track how subscription fees or engagement tactics evolve across niches and timeframes.

And yes—all of this assumes you're working with publicly available data, never private content or protected media.

Legal & Ethical Considerations (Yes, You Must Read This)

Scraping data online always comes with responsibility. With OnlyFans, you’re working in a platform that has explicit terms about user data, privacy, and copyright.

Here’s how to stay on the right side of the law and ethics:

• Only collect data that’s publicly visible to you as a logged-in user. Do not attempt to bypass paywalls or protected content.
• Respect copyright laws. Don’t save or redistribute images, videos, or exclusive text—even if it appears visible to you.
• Follow the platform’s robots.txt file and terms of service when automating data collection.
• Don’t overwhelm the site. Use delays, rotate IPs responsibly, and avoid scraping patterns that might lead to rate limiting or bans.
• Use proxies ethically. The point isn’t to hide malicious intent—it’s to avoid being blocked for legitimate access at scale.

If in doubt, ask: Would I feel comfortable explaining this approach to a legal team or the creators I’m analyzing? If the answer is no, rethink your methods.

Method 1: Using Browser Automation Tools (Perfect for Beginners)

Browser automation is a great place to start—especially when working with dynamic content that requires JavaScript rendering or authentication.

Option 1: Axiom.ai (No-Code Browser Bot)

Axiom.ai is a Chrome extension that lets you build scraping workflows without writing any code. Think of it as a “point-and-click” scraping tool, ideal for extracting public creator data you can see after logging in.

The process looks like this:

1. Install the Axiom Chrome extension.
2. Log into OnlyFans with your account.
3. Launch Axiom, build a new automation by selecting profile elements like usernames or subscription prices.
4. Export your data to Google Sheets or CSV.

// Example of what Axiom generates behind the scenes
async function scrapeOnlyFansProfiles() {
  await page.goto('https://onlyfans.com/');
  await page.login(); // You'll need to be logged in
  
  // Navigate to subscriptions page
  await page.goto('https://onlyfans.com/my/subscriptions');
  
  // Extract creator information
  const creators = await page.evaluate(() => {
    return Array.from(document.querySelectorAll('.g-user-name')).map(el => ({
      username: el.textContent.trim(),
      profileUrl: el.href
    }));
  });
  
  // Export to Google Sheets
  await exportToSheet(creators, 'OnlyFans Creators');
}

This is especially useful for:

• Exporting your own subscription list
• Collecting profile URLs and names
• Monitoring public bios or price changes

Option 2: Puppeteer for Full Control

Want more precision and repeatability? Puppeteer (Node.js-based) gives you full control over a headless or visible browser session. It lets you programmatically navigate to profiles, wait for elements to load, and extract what you need.

This method is better suited for developers who want to:

• Scrape profiles in bulk
• Handle dynamic content
• Customize authentication, headers, and scroll behavior

const puppeteer = require('puppeteer');

async function scrapeOnlyFans() {
  const browser = await puppeteer.launch({ headless: false });
  const page = await browser.newPage();
  
  // Set user agent to avoid detection
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36');
  
  // Login (you'll need to handle this manually or with credentials)
  await page.goto('https://onlyfans.com/');
  console.log('Please log in manually within the browser window...');
  await page.waitForNavigation({ waitUntil: 'networkidle0', timeout: 60000 });
  
  // Navigate to a creator's profile you have access to
  await page.goto('https://onlyfans.com/creatorusername');
  await page.waitForSelector('.g-user-name');
  
  // Extract basic profile data
  const profileData = await page.evaluate(() => {
    return {
      name: document.querySelector('.g-user-name')?.textContent.trim(),
      bio: document.querySelector('.b-profile__text')?.textContent.trim(),
      subscriptionPrice: document.querySelector('.b-price')?.textContent.trim(),
      postsCount: document.querySelector('.b-profile__sections__count')?.textContent.trim()
    };
  });
  
  console.log(profileData);
  await browser.close();
}

scrapeOnlyFans().catch(console.error);

You’ll still need to log in manually (or automate it with caution), but it opens up far more control than no-code tools.

Method 2: Scraping OnlyFans with Python, Requests, and BeautifulSoup

If you’re technically inclined, scraping with Python offers flexibility and performance. But OnlyFans’ modern web architecture means basic scraping won’t cut it. You need to mimic browser sessions, manage authentication cookies, and possibly access internal APIs.

First, Set Up Your Environment

You’ll need:

• requests for HTTP requests
• BeautifulSoup for parsing HTML (if needed)
• pandas for handling data
• Valid session cookies (extracted manually after login)
• Browser headers that match a real user-agent

import requests
from bs4 import BeautifulSoup
import json
import time
import random
import pandas as pd

# Session to maintain cookies
session = requests.Session()

# Headers to mimic a real browser
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8',
    'Accept-Language': 'en-US,en;q=0.9',
    'Referer': 'https://onlyfans.com/',
    'Origin': 'https://onlyfans.com'
}

session.headers.update(headers)

Once your session is authenticated, you can make calls to known API endpoints (e.g., /api2/v2/users/{username}) to extract public data.

def setup_auth_session():
    # These values need to be extracted manually after logging in
    auth_cookies = {
        'sess': 'your_sess_cookie',
        'auth_id': 'your_auth_id_cookie',
        # Add other required cookies
    }
    
    # Add cookies to session
    for key, value in auth_cookies.items():
        session.cookies.set(key, value)
        
    # Add special headers required by OnlyFans
    session.headers.update({
        'app-token': '33d57ade8c02dbc5a333db99ff9ae26a',  # This is a common app token
        'x-bc': 'your_x_bc_value'
    })
    
    return session

This method is ideal if you want to:

• Collect structured data across multiple profiles
• Monitor price, post count, or bio changes
• Analyze trends across time

How to scrape creator profiles:

def scrape_creator_profile(username):
    session = setup_auth_session()
    
    # For API-based approach (more reliable)
    url = f"https://onlyfans.com/api2/v2/users/{username}"
    
    response = session.get(url)
    if response.status_code == 200:
        data = response.json()
        profile_info = {
            'username': data.get('username'),
            'name': data.get('name'),
            'subscription_price': data.get('subscriptionPrice'),
            'posts_count': data.get('postsCount'),
            'photos_count': data.get('photosCount'),
            'videos_count': data.get('videosCount')
        }
        return profile_info
    else:
        print(f"Failed to fetch profile: {response.status_code}")
        return None

# Usage
profile = scrape_creator_profile('username')
print(profile)

or how to scrape public posts:

def scrape_creator_posts(username, limit=10):
    session = setup_auth_session()
    
    url = f"https://onlyfans.com/api2/v2/users/{username}/posts?limit={limit}"
    
    response = session.get(url)
    if response.status_code == 200:
        posts = response.json()
        extracted_posts = []
        
        for post in posts:
            post_data = {
                'id': post.get('id'),
                'text': post.get('text'),
                'created_at': post.get('createdAt'),
                'likes_count': post.get('likesCount'),
                'comments_count': post.get('commentsCount'),
                'media_count': len(post.get('media', [])),
                'price': post.get('price')
            }
            extracted_posts.append(post_data)
        
        return extracted_posts
    else:
        print(f"Failed to fetch posts: {response.status_code}")
        return None

# Usage
posts = scrape_creator_posts('username', 20)
df = pd.DataFrame(posts)
df.to_csv('creator_posts.csv', index=False)

Just remember: API endpoints and required headers/cookies change frequently. Keep your scripts up to date.

Method 3: Use a Scraping API for Reliability

If you want a scalable and managed solution, consider using a scraping API that supports headless browsers and JavaScript rendering.

Platforms like Decodo, Bright Data, or ScraperAPI offer:

• Rotating residential proxies
• JavaScript rendering
• Automated CAPTCHA handling
• Data extraction via CSS selectors or XPath

import requests

def scrape_with_api():
    # API configuration
    api_key = "YOUR_DECODO_API_KEY"
    
    # Target URL
    target_url = "https://onlyfans.com/username"
    
    # API endpoint
    api_endpoint = "https://api.decodo.com/v1/scrape"
    
    # Request parameters
    params = {
        "api_key": api_key,
        "url": target_url,
        "country": "us",
        "render_js": True,
        "extract": {
            "profile": {
                "selector": ".profile-header",
                "multiple": False,
                "extract": {
                    "name": ".profile-name",
                    "bio": ".profile-bio",
                    "subscription": ".price-amount"
                }
            },
            "posts": {
                "selector": ".post-item",
                "multiple": True,
                "extract": {
                    "text": ".post-text",
                    "date": ".post-date",
                    "likes": ".likes-count"
                }
            }
        }
    }
    
    # Make the request
    response = requests.post(api_endpoint, json=params)
    
    # Process the results
    if response.status_code == 200:
        data = response.json()
        return data
    else:
        print(f"Error: {response.status_code}")
        return None

This is a smart move if you're:

• Scraping at scale
• Targeting multiple profiles
• Wanting to avoid the pain of maintaining your own proxy pool

APIs like Decodo even let you define structured data you want to extract from each page—bio, subscription cost, posts—without writing custom scrapers for every new layout update.

How to Handle Authentication on OnlyFans (Still Tricky in 2025)

OnlyFans has a layered authentication model involving:

• Session cookies (sess, auth_id, etc.)
• API headers (app-token, x-bc, etc.)
• Client-side token verification

To authenticate a scraping session:

1. Log in manually in your browser.
2. Use browser dev tools to extract the relevant cookies.
3. Inject them into your script’s session.
4. Include all required headers to mimic a real client.

You’ll also want to monitor your session’s expiry and refresh tokens when possible. This isn’t always easy—but it’s necessary for deeper scraping that goes beyond what’s publicly accessible on landing pages.

Dealing With Rate Limits and IP Blocks

OnlyFans is aggressive with anti-scraping measures, so here’s how to stay under the radar:

1. Randomized delays: Never send requests in tight loops. Sleep 2–5 seconds (or longer) between calls.

def make_request(url):
    # Random delay between 2-5 seconds
    time.sleep(random.uniform(2, 5))
    return session.get(url)

2. Proxy rotation: Use residential IPs, rotate them periodically, and avoid patterns. We would recommend Roundproxies.

from random import choice

proxies = [
    "http://proxy1:port",
    "http://proxy2:port",
    "http://proxy3:port"
]

def request_with_proxy(url):
    proxy = {"http": choice(proxies), "https": choice(proxies)}
    return session.get(url, proxies=proxy)

3. Exponential backoff: If you’re rate-limited (HTTP 429), double your delay each time before retrying.

def request_with_backoff(url, max_retries=5):
    for attempt in range(max_retries):
        response = session.get(url)
        if response.status_code == 200:
            return response
        
        # If rate limited, wait with exponential backoff
        if response.status_code == 429:
            sleep_time = 2 ** attempt  # 1, 2, 4, 8, 16...
            print(f"Rate limited. Waiting {sleep_time} seconds...")
            time.sleep(sleep_time)
    
    return None  # Max retries exceeded

4. Limit concurrency: Don’t run 50 threads at once. Start with 1–2 and scale carefully.
5. CAPTCHA handling: Sometimes unavoidable. Consider using 3rd-party CAPTCHA solvers or manual intervention if needed.

The more you behave like a real user, the safer you’ll be.

Storing & Processing Your OnlyFans Data

Once your scraping logic works, the next challenge is: how do I store and use the data effectively?

You’ve got options:

• JSON for structured storage
• CSV or Excel for quick inspection
• Pandas DataFrames for analysis
• Databases (SQLite, PostgreSQL) for scalable storage

def save_data(data, filename='onlyfans_data.json'):
    # Save as JSON
    with open(filename, 'w', encoding='utf-8') as f:
        json.dump(data, f, ensure_ascii=False, indent=4)
    
    # Convert to DataFrame for analysis
    df = pd.json_normalize(data)
    
    # Save as CSV
    df.to_csv(f"{filename.split('.')[0]}.csv", index=False)
    
    return df

For quick wins, use pandas to normalize your scraped data and output both .json and .csv versions. This makes it easier to visualize changes over time—like subscription trends or post engagement metrics.

Common Scraping Challenges on OnlyFans

Scraping OnlyFans isn't plug-and-play. Here are the most common roadblocks and how to handle them:

Final Thoughts: Scrape Responsibly, Use Ethically

Learning how to scrape OnlyFans in 2025 is more about strategy and responsibility than just code. The platform’s protections are designed to safeguard creators, so your scraping should never cross that line.

When done right, public scraping can offer powerful insights for research, pricing intelligence, and platform studies. But it must always respect privacy, copyright, and platform rules.

If your goal is ethical data collection, you now have the blueprint to do it.