TL;DR
Scrape.do is built around one goal: get the HTML, no matter what. Their proxy network of 110M+ IPs and 99.98% success rate reflects serious investment in anti-detection infrastructure. KnowledgeSDK prioritizes a different goal: turn that content into something AI agents can immediately use — markdown, structured knowledge, semantic search, and change monitoring.
| Feature | Scrape.do | KnowledgeSDK |
|---|---|---|
| Proxy pool size | 110M+ IPs | Standard |
| Success rate guarantee | 99.98% | Standard |
| Pay-per-success billing | Yes | No |
| Raw HTML output | Yes | No |
| Markdown output | No | Yes |
| JS rendering | Yes | Yes |
| Anti-bot bypass | Yes | Yes |
| Semantic search | No | Yes |
| Webhooks | No | Yes |
| MCP server | No | Yes |
What Each Tool Actually Does
Scrape.do is a proxy-first scraping API with one of the largest residential proxy networks in the industry — over 110 million IPs across 195 countries. Their 99.98% success rate claim reflects the depth of their anti-bot infrastructure: rotating residential proxies, custom fingerprinting, and headless browser rendering for JS-heavy sites. They bill on a pay-per-success model, meaning you do not pay for failed requests. For teams whose primary problem is getting blocked, Scrape.do directly addresses that pain.
The output is raw HTML. Scrape.do does not transform, clean, or index the content. It delivers the page source and leaves the rest to you. This is the right design for teams with existing HTML parsing pipelines — but it means building the markdown conversion, knowledge extraction, storage, and search layers yourself.
KnowledgeSDK has a smaller proxy footprint than Scrape.do, which is an honest weakness for the most aggressively anti-bot sites. What it trades for is a complete output pipeline: the API returns clean markdown, indexes it with semantic embeddings, and makes it searchable via POST /v1/search. Webhooks let you set up change detection on monitored pages without polling. For most publicly accessible pages, KnowledgeSDK's anti-bot handling is sufficient — the gap only matters for the hardest targets.
Pricing
| Plan | Scrape.do | KnowledgeSDK |
|---|---|---|
| Free | 1,000 credits | 1,000 requests |
| Entry | ~$29 / month | $29 / month (Starter) |
| Mid-tier | ~$99 / month | $99 / month (Pro) |
| High-volume | Custom | Custom |
Both tools have comparable base pricing. Scrape.do's pay-per-success model can be economical for high-failure-rate targets. KnowledgeSDK's flat per-request pricing is more predictable for standard workloads where most pages load successfully.
Feature Comparison
| Feature | Scrape.do | KnowledgeSDK |
|---|---|---|
| Proxy pool (IPs) | 110M+ | Standard |
| Geographic proxy targeting | Yes (195 countries) | Limited |
| Pay-per-success | Yes | No |
| Raw HTML | Yes | No |
| Clean markdown | No | Yes |
| JS rendering | Yes | Yes |
| Anti-bot bypass | Yes (strongest) | Yes |
| Structured extraction | No | Yes |
| Semantic search | No | Yes |
| Knowledge indexing | No | Yes |
| Webhooks | No | Yes |
| MCP server | No | Yes |
| Screenshot | No | Yes |
| SDK | Yes | Yes (Node, Python) |
When Scrape.do Wins
- You are scraping sites with aggressive anti-bot systems (Cloudflare Enterprise, DataDome, Akamai)
- You need geographic proxy diversity across 195 countries
- Your pipeline consumes raw HTML and you have existing parsers
- Pay-per-success billing matters because your target sites have high failure rates
- Volume is very high and proxy rotation is the primary engineering challenge
When KnowledgeSDK Wins
- Your target pages are publicly accessible without heavy bot protection
- You want LLM-ready markdown, not raw HTML
- You need semantic search over scraped content without building a search stack
- Change detection webhooks are part of your workflow
- You are building for AI agents and need MCP server integration
- You want the full pipeline — scrape, extract, index, search — in one API
The Practical Trade-off
If your biggest engineering challenge is bypassing bot detection at scale, Scrape.do's proxy infrastructure is difficult to match. If your biggest challenge is turning web content into something your AI system can reason over, KnowledgeSDK saves you from building a substantial amount of infrastructure.
Many teams discover they need both: Scrape.do for the hardest scraping targets, KnowledgeSDK for everything else plus the knowledge layer.
Code Example
import KnowledgeSDK from "@knowledgesdk/node";
const client = new KnowledgeSDK({ apiKey: "knowledgesdk_live_..." });
// Extract and index a page
await client.extract("https://competitor.com/pricing");
// Set a webhook to detect price changes
await client.webhooks.create({
url: "https://yourapp.com/webhooks/changes",
events: ["knowledge.updated"],
projectId: "proj_monitoring"
});
// Search the indexed knowledge
const results = await client.search({
query: "enterprise pricing tiers",
projectId: "proj_monitoring"
});
Final Verdict
Scrape.do is the right choice when anti-bot infrastructure is the bottleneck — 110M+ IPs and a 99.98% success rate are hard to argue with for truly hostile scraping targets. KnowledgeSDK is the right choice when you need the content to be immediately usable by an AI system. For most public web pages, KnowledgeSDK's anti-bot handling is sufficient, and the semantic search, markdown output, and webhooks save you from building a substantial backend on top of raw HTML.