Proxies for NFT Marketplace Scraping (OpenSea, Blur, Magic Eden)

NFT marketplace data powers trading algorithms, rarity analysis tools, portfolio trackers, and market research platforms. OpenSea, Blur, and Magic Eden collectively host millions of NFTs with constantly changing floor prices, listing activity, and sales data. Scraping this data at scale requires proxy infrastructure that handles aggressive anti-bot protections while maintaining the throughput needed for real-time market monitoring.

This guide covers the technical requirements for scraping each major NFT marketplace, including proxy selection, anti-detection strategies, and practical code examples.

Why NFT Marketplace Scraping Requires Proxies

NFT marketplaces implement multiple layers of anti-scraping protection:

Cloudflare Bot Management: OpenSea and Magic Eden use Cloudflare’s enterprise bot detection, which fingerprints browsers, analyzes request patterns, and serves CAPTCHAs to suspicious traffic.
API Rate Limits: OpenSea’s API limits requests to 5 per second on free tiers. Even paid tiers cap at 30 requests per second.
IP Reputation Scoring: Marketplaces track request volume per IP and progressively degrade service for high-volume IPs before eventually blocking them.
JavaScript Challenges: Many marketplace pages require JavaScript execution to render content, blocking simple HTTP scrapers.

Without proxies, a scraper monitoring even a modest collection of 100 NFT projects will exhaust rate limits and trigger blocks within minutes.

For comprehensive guidance on web scraping with proxies, including rotation patterns and anti-detection fundamentals, the dedicated guide covers the technical foundation.

Proxy Selection for NFT Scraping

By Marketplace

Marketplace	Recommended Proxy	Reason
OpenSea	Mobile proxies	Cloudflare enterprise + aggressive fingerprinting
Blur	Mobile proxies	Heavy bot detection + Cloudflare
Magic Eden	Residential or mobile	Less aggressive but still Cloudflare-protected
LooksRare	Residential	Moderate protection
Tensor (Solana)	Residential	API-first approach, moderate limits

Mobile proxies consistently outperform other types for NFT scraping because Cloudflare assigns the highest trust scores to mobile carrier IPs. This means fewer CAPTCHAs, fewer blocks, and higher sustained throughput.

Scraping OpenSea

Using the OpenSea API

OpenSea provides a REST API that is the primary target for data collection:

import aiohttp
import asyncio
import time
from typing import List, Dict, Optional

class OpenSeaScraper:
    BASE_URL = "https://api.opensea.io/api/v2"

    def __init__(self, api_keys: list, proxy_pool: list):
        self.api_keys = api_keys
        self.proxy_pool = proxy_pool
        self.key_index = 0
        self.proxy_index = 0

    def _get_headers(self) -> dict:
        key = self.api_keys[self.key_index % len(self.api_keys)]
        self.key_index += 1
        return {
            "accept": "application/json",
            "x-api-key": key,
        }

    def _get_proxy(self) -> str:
        proxy = self.proxy_pool[self.proxy_index % len(self.proxy_pool)]
        self.proxy_index += 1
        return proxy

    async def get_collection_stats(self, session, collection_slug):
        """Fetch collection statistics."""
        url = f"{self.BASE_URL}/collections/{collection_slug}/stats"
        proxy = self._get_proxy()

        async with session.get(
            url,
            headers=self._get_headers(),
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                data = await resp.json()
                return {
                    "collection": collection_slug,
                    "floor_price": data.get("total", {}).get("floor_price"),
                    "total_volume": data.get("total", {}).get("volume"),
                    "total_sales": data.get("total", {}).get("sales"),
                    "num_owners": data.get("total", {}).get("num_owners"),
                    "market_cap": data.get("total", {}).get("market_cap"),
                    "timestamp": time.time()
                }
            elif resp.status == 429:
                await asyncio.sleep(2)
                return None
            return None

    async def get_collection_listings(self, session, collection_slug,
                                       limit=50):
        """Fetch active listings for a collection."""
        url = f"{self.BASE_URL}/listings/collection/{collection_slug}/all"
        proxy = self._get_proxy()
        params = {"limit": limit}

        async with session.get(
            url,
            headers=self._get_headers(),
            params=params,
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                data = await resp.json()
                listings = []
                for listing in data.get("listings", []):
                    price_data = listing.get("price", {}).get("current", {})
                    listings.append({
                        "token_id": listing.get("protocol_data", {})
                            .get("parameters", {}).get("offer", [{}])[0]
                            .get("identifierOrCriteria"),
                        "price_eth": float(price_data.get("value", 0)) / 1e18,
                        "currency": price_data.get("currency"),
                        "expiration": listing.get("protocol_data", {})
                            .get("parameters", {}).get("endTime"),
                    })
                return listings
            return []

    async def get_collection_events(self, session, collection_slug,
                                     event_type="sale"):
        """Fetch recent sales or other events."""
        url = f"{self.BASE_URL}/events/collection/{collection_slug}"
        proxy = self._get_proxy()
        params = {"event_type": event_type, "limit": 50}

        async with session.get(
            url,
            headers=self._get_headers(),
            params=params,
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                return await resp.json()
            return None

Scraping OpenSea’s Web Interface

When API limits are insufficient, scraping the web interface provides additional data. This requires a headless browser:

from playwright.async_api import async_playwright

class OpenSeaWebScraper:
    async def scrape_collection_page(self, collection_slug: str,
                                      proxy: str):
        async with async_playwright() as p:
            browser = await p.chromium.launch(
                headless=True,
                proxy={
                    "server": f"http://{proxy.split('@')[1]}",
                    "username": proxy.split(':')[0],
                    "password": proxy.split(':')[1].split('@')[0],
                }
            )

            context = await browser.new_context(
                viewport={"width": 1920, "height": 1080},
                user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
                          "AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36"
            )

            page = await context.new_page()
            await page.goto(
                f"https://opensea.io/collection/{collection_slug}",
                wait_until="networkidle"
            )

            # Wait for listings to load
            await page.wait_for_selector('[data-testid="ItemCard"]',
                                          timeout=15000)

            # Extract listing data
            listings = await page.evaluate('''() => {
                const cards = document.querySelectorAll(
                    '[data-testid="ItemCard"]'
                );
                return Array.from(cards).map(card => ({
                    name: card.querySelector(
                        '[data-testid="ItemCardFooter-name"]'
                    )?.textContent,
                    price: card.querySelector(
                        '[data-testid="ItemCardPrice"]'
                    )?.textContent,
                }));
            }''')

            await browser.close()
            return listings

Scraping Blur

Blur’s API is less documented than OpenSea’s but provides valuable data for NFT traders:

class BlurScraper:
    BASE_URL = "https://core-api.prod.blur.io/v1"

    def __init__(self, proxy_pool: list):
        self.proxy_pool = proxy_pool
        self.proxy_index = 0

    def _get_proxy(self):
        proxy = self.proxy_pool[self.proxy_index % len(self.proxy_pool)]
        self.proxy_index += 1
        return proxy

    async def get_collection_stats(self, session, contract_address):
        url = f"{self.BASE_URL}/collections/{contract_address}"
        proxy = self._get_proxy()

        headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
                          "AppleWebKit/537.36 Chrome/120.0.0.0",
            "Accept": "application/json",
            "Origin": "https://blur.io",
            "Referer": "https://blur.io/",
        }

        async with session.get(
            url,
            headers=headers,
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                data = await resp.json()
                collection = data.get("collection", {})
                return {
                    "contract": contract_address,
                    "floor_price": collection.get("floorPrice"),
                    "total_supply": collection.get("totalSupply"),
                    "num_owners": collection.get("numberOwners"),
                    "volume_24h": collection.get("volume24h"),
                    "source": "blur"
                }
            return None

    async def get_floor_listings(self, session, contract_address):
        url = f"{self.BASE_URL}/collections/{contract_address}/tokens"
        proxy = self._get_proxy()
        params = {"sort": "price", "order": "asc", "limit": 50}

        headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
                          "AppleWebKit/537.36 Chrome/120.0.0.0",
            "Origin": "https://blur.io",
            "Referer": "https://blur.io/",
        }

        async with session.get(
            url,
            headers=headers,
            params=params,
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                data = await resp.json()
                return data.get("tokens", [])
            return []

Scraping Magic Eden

class MagicEdenScraper:
    # Ethereum collections
    ETH_BASE = "https://api-mainnet.magiceden.dev/v3/rtp/ethereum"
    # Solana collections
    SOL_BASE = "https://api-mainnet.magiceden.dev/v2"

    def __init__(self, proxy_pool: list, api_key: str = None):
        self.proxy_pool = proxy_pool
        self.api_key = api_key
        self.proxy_index = 0

    def _get_proxy(self):
        proxy = self.proxy_pool[self.proxy_index % len(self.proxy_pool)]
        self.proxy_index += 1
        return proxy

    async def get_solana_collection_stats(self, session, symbol):
        url = f"{self.SOL_BASE}/collections/{symbol}/stats"
        proxy = self._get_proxy()
        headers = {}
        if self.api_key:
            headers["Authorization"] = f"Bearer {self.api_key}"

        async with session.get(
            url, headers=headers,
            proxy=f"http://{proxy}",
            timeout=aiohttp.ClientTimeout(total=10)
        ) as resp:
            if resp.status == 200:
                data = await resp.json()
                return {
                    "symbol": symbol,
                    "floor_price_sol": data.get("floorPrice", 0) / 1e9,
                    "listed_count": data.get("listedCount"),
                    "volume_all": data.get("volumeAll", 0) / 1e9,
                    "avg_price_24h": data.get("avgPrice24hr", 0) / 1e9,
                    "source": "magic_eden"
                }
            return None

Multi-Marketplace Aggregator

class NFTMarketAggregator:
    def __init__(self, proxy_pool: list, opensea_keys: list):
        self.opensea = OpenSeaScraper(opensea_keys, proxy_pool)
        self.blur = BlurScraper(proxy_pool)
        self.magic_eden = MagicEdenScraper(proxy_pool)

    async def get_collection_overview(self, collection_slug: str,
                                       contract_address: str):
        """Get data from all marketplaces for a single collection."""
        async with aiohttp.ClientSession() as session:
            tasks = {
                "opensea": self.opensea.get_collection_stats(
                    session, collection_slug
                ),
                "blur": self.blur.get_collection_stats(
                    session, contract_address
                ),
            }

            results = {}
            for source, task in tasks.items():
                try:
                    results[source] = await task
                except Exception as e:
                    results[source] = {"error": str(e)}

            return results

    async def monitor_collections(self, collections: list,
                                    interval: float = 30):
        """Continuously monitor multiple collections."""
        while True:
            for col in collections:
                data = await self.get_collection_overview(
                    col["slug"], col["contract"]
                )
                # Store or process data
                print(f"{col['slug']}: {data}")

            await asyncio.sleep(interval)

Proxy Sizing Recommendations

Scraping Scope	Collections	Data Points	Proxies Needed
Hobby tracker	5-10	Floor prices	2-3 mobile
Trading tool	50-100	Full listings + sales	5-10 mobile
Analytics platform	500+	All available data	15-30 mobile
Enterprise	5,000+	Complete market data	50+ mobile

Handling Cloudflare Challenges

When Cloudflare serves a challenge page, your scraper needs to solve it. Options include:

Use headless browsers with stealth plugins for web scraping
Switch to a fresh mobile proxy — often the challenge is IP-specific
Implement CAPTCHA solving services as a fallback

The best approach is prevention: mobile proxies trigger far fewer Cloudflare challenges than other proxy types, and rotating IPs before hitting challenge thresholds keeps your scraper running smoothly.

Data Storage Best Practices

Store NFT market data in a time-series format for historical analysis:

import sqlite3

def init_nft_db(db_path: str):
    conn = sqlite3.connect(db_path)
    conn.execute('''CREATE TABLE IF NOT EXISTS floor_prices (
        id INTEGER PRIMARY KEY AUTOINCREMENT,
        collection TEXT NOT NULL,
        marketplace TEXT NOT NULL,
        floor_price REAL,
        volume_24h REAL,
        listed_count INTEGER,
        timestamp REAL NOT NULL
    )''')
    conn.execute('''CREATE INDEX IF NOT EXISTS idx_collection_ts
                    ON floor_prices(collection, timestamp)''')
    conn.commit()
    return conn

For a technical overview of proxy rotation and how different proxy types handle rate limiting, the glossary provides useful background.

Conclusion

NFT marketplace scraping is a demanding use case that requires the right combination of proxy infrastructure, anti-detection techniques, and marketplace-specific scraping logic. Mobile proxies provide the trust scores needed to bypass Cloudflare protection on OpenSea and Blur, while proper rate limiting and request distribution ensure sustained access. Start with API-based scraping and fall back to headless browser scraping only when API limits are insufficient for your data needs.