ScrapFly earns its reputation on anti-bot bypass and excellent docs. WebScraping.AI offers the same core job — rendered pages through datacenter, residential, or stealth proxies plus AI extraction — with flatter, cheaper credit math and 7 official SDKs.
2,000 free API credits · No credit card required
An honest, side-by-side comparison. Verify the numbers — this is a market where you should.
| WebScraping.AI | ScrapFly | |
|---|---|---|
| Entry plan | $29/mo · 250,000 credits | $30/mo · 200,000 credits (Discovery) |
| Plain request (datacenter) | 1 credit | 1 credit |
| JS (Chromium) rendering | 5 credits | +5 credits |
| Residential proxies | 10 credits (25 with JS) | 25 credits (30 with JS) |
| Stealth / anti-bot tier | 50 credits, fixed | ASP: dynamic credit cost per request |
| Billing on failures | Free — always, no threshold | Free under "Scrape Failed Protection" (reverts to billed if >30% of traffic fails in an hour) |
| Natural-language Q&A (<code>/ai/question</code>) | Yes | — (extraction via prompt/schema) |
| AI field extraction | Yes (/ai/fields) |
Yes (Extraction API, billed as add-on) |
| LLM-ready text | Yes (/text) |
Yes (markdown format) |
| Official SDKs | 7 (Python, JS, PHP, Ruby, Go, Java, C#) | Python & TypeScript |
| First-party MCP server | Yes | Yes |
| Screenshot API | — | Yes |
Pricing and credit costs last checked July 2026. Sources: ScrapFly pricing · WebScraping.AI pricing.
No tool is right for everyone. ScrapFly is a capable product, and these are the areas where it genuinely shines — worth weighing before you switch.
The most common reasons teams evaluate a switch.
Residential proxies cost 25 credits and JS adds 5 more on ScrapFly, so a protected, JS-rendered scrape burns 30 credits — the 200k-credit Discovery plan collapses to ~6,600 such requests, and users report bills quietly tripling. WebScraping.AI's same configuration costs 25 credits on a 250k-credit $29 plan, and residential without JS is 10 credits, not 25.
ScrapFly's anti-bot bypass consumes a variable number of credits depending on what the target requires, which makes hard-site budgets unpredictable. WebScraping.AI's stealth tier is a flat 50 credits per request — expensive targets are at least predictably expensive.
ScrapFly's Scrape Failed Protection stops applying once more than 30% of your traffic fails within an hour — exactly the scenario you're in when a target starts blocking you. WebScraping.AI simply never bills a failed request, with no fairness threshold.
Exhaust Discovery's 200k credits and you're done for the month unless you upgrade tiers. WebScraping.AI's plans are self-serve and adjustable at any time, and more of your credits survive contact with real-world targets thanks to the flatter multipliers.
Every request type has a fixed, published credit cost — no surprises, and you only pay for successful requests.
Plans from $29/mo (250k credits) · $99/mo (1M) · $249/mo (3M). Failed requests are always free. See full pricing.
Both products use credit multipliers — that's the market standard. The difference is where the multipliers sit. On ScrapFly, the moment a site needs residential IPs you're at 25 credits, and 30 with rendering. On WebScraping.AI, residential is 10 credits (25 with JS), and the whole table is published: 1 / 5 / 10 / 25 / 50, +5 for AI extraction.
Concretely, 100k JS-rendered residential requests cost 3M credits on ScrapFly's model (30 each) versus 2.5M on ours (25 each) — and each plan dollar buys more credits to begin with (250k at $29 vs 200k at $30). Every request that fails along the way costs you nothing, unconditionally.
ScrapFly's Extraction API is capable — prompts, schemas, and auto-extract models. WebScraping.AI adds the endpoint developers reach for first when prototyping: /ai/question. Ask "what's the price?" or "is this in stock?" about any URL and get the answer back as a string — no schema required. When you're ready for structure, /ai/fields returns typed JSON for the fields you name.
Both ship first-party MCP servers, so the choice isn't about AI-agent readiness — it's about how much credit math and schema ceremony sits between you and the data.
Point your requests at WebScraping.AI — here's the equivalent call in your language.
curl -G "https://api.webscraping.ai/ai/fields" \
--data-urlencode "api_key=YOUR_API_KEY" \
--data-urlencode "url=https://example.com/product" \
--data-urlencode "fields[title]=Product title" \
--data-urlencode "fields[price]=Current price with currency" \
--data-urlencode "fields[availability]=In stock or out of stock"
# Response:
# {
# "title": "Example Product",
# "price": "$99.99",
# "availability": "in stock"
# }
# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client
client = Client(api_key="YOUR_API_KEY")
result = client.fields(
"https://example.com/product",
fields={
"title": "Product title",
"price": "Current price with currency",
"availability": "In stock or out of stock",
},
)
print(result)
# Response:
# {
# "title": "Example Product",
# "price": "$99.99",
# "availability": "in stock"
# }
// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';
const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
url: 'https://example.com/product',
fields: {
title: 'Product title',
price: 'Current price with currency',
availability: 'In stock or out of stock',
},
});
console.log(result);
// Response:
// {
// "title": "Example Product",
// "price": "$99.99",
// "availability": "in stock"
// }
<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';
use WebScrapingAI\Client;
$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://example.com/product', [
'title' => 'Product title',
'price' => 'Current price with currency',
'availability' => 'In stock or out of stock',
]);
print_r($result);
// Response:
// {
// "title": "Example Product",
// "price": "$99.99",
// "availability": "in stock"
// }
# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'
client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
'https://example.com/product',
fields: {
title: 'Product title',
price: 'Current price with currency',
availability: 'In stock or out of stock',
}
)
puts result.inspect
# Response:
# {
# "title": "Example Product",
# "price": "$99.99",
# "availability": "in stock"
# }
// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main
import (
"context"
"fmt"
webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)
func main() {
client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
URL: "https://example.com/product",
Fields: map[string]string{
"title": "Product title",
"price": "Current price with currency",
"availability": "In stock or out of stock",
},
})
fmt.Println(result.Result)
}
// Response:
// {
// "title": "Example Product",
// "price": "$99.99",
// "availability": "in stock"
// }
// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;
Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
.url("https://example.com/product")
.addField("title", "Product title")
.addField("price", "Current price with currency")
.addField("availability", "In stock or out of stock")
.build());
System.out.println(result.getResult());
// Response:
// {
// "title": "Example Product",
// "price": "$99.99",
// "availability": "in stock"
// }
// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;
var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
Url = "https://example.com/product",
Fields = new Dictionary<string, string> {
["title"] = "Product title",
["price"] = "Current price with currency",
["availability"] = "In stock or out of stock",
},
});
Console.WriteLine(result.Result);
// Response:
// {
// "title": "Example Product",
// "price": "$99.99",
// "availability": "in stock"
// }
Is WebScraping.AI a good ScrapFly alternative?
For most scraping workloads, yes: the same datacenter/residential/stealth proxy tiers and JS rendering with flatter credit costs (residential at 10 credits vs 25), unconditionally free failed requests, AI question answering and field extraction, and 7 official SDKs. ScrapFly keeps the edge on its specialized ASP anti-bot bypass and screenshot tooling.
How do the credit models compare?
Both use multipliers. WebScraping.AI: 1 credit plain, 5 with JS, 10 residential (25 with JS), 50 stealth, +5 for AI — all fixed and published. ScrapFly: 1 credit plain, +5 for JS, 25 residential, and a dynamic credit cost when ASP engages. Entry plans are $29/mo for 250k credits here vs $30/mo for 200k there.
Does ScrapFly charge for failed requests?
Normally no — its Scrape Failed Protection covers failures with eligible status codes. But the protection is suspended when more than 30% of your traffic fails within an hour, which is precisely what a blocking event looks like. WebScraping.AI never bills failed requests, with no threshold or fine print.
Does WebScraping.AI handle anti-bot systems like ScrapFly's ASP?
Hard targets route through rotating residential proxies (10–25 credits) or stealth proxies (50 credits) designed for protected-site scraping. ScrapFly's ASP is a strong specialized system and may win on the most aggressively protected sites; the difference is our cost is flat and known before you send the request.
Can I use WebScraping.AI with AI agents like ScrapFly's MCP?
Yes — both ship first-party MCP servers. WebScraping.AI's exposes question answering, field extraction, HTML/text retrieval, and CSS-selector tools to Claude, Cursor, and other MCP clients, with an optional content-sandboxing mode against prompt injection.
Get started with 2,000 free API credits. No credit card required.