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Olostep vs ScrapeGraphAI

Web Scraping

Olostep
Olostep
100
VS
ScrapeGraphAI
100
ScrapeGraphAI
Metric Olostep ScrapeGraphAI
Category Web Scraping Web Scraping
Pricing Freemium Freemium
Auth API Key API Key
Format JSON JSON
Bot Blocking None None
OpenAPI Spec Yes Yes
Credit Card Not required Not required
Rate Limit 5 RPM (free), 150-500 concurrent (paid) 10 RPM (free), 30 RPM (starter), 60 RPM (growth), 200 RPM (pro)
Score Component Olostep ScrapeGraphAI
Base +50 +50
OpenAPI Spec +15 (Yes) +15 (Yes)
Auth +10 (API Key) +10 (API Key)
Format +10 (JSON) +10 (JSON)
Bot Blocking +10 (None) +10 (None)
No CC +5 (Yes) +5 (Yes)
Free 0 (No) 0 (No)
Total 100 100
Olostep ScrapeGraphAI
Pros
  • + Returns clean markdown/JSON natively — no HTML parsing needed by agents
  • + Official Python & Node SDKs plus MCP server for direct agent integration
  • + Comprehensive OpenAPI specs per endpoint group enabling auto-tooling
  • + Natural language prompts replace CSS selectors — agents describe what they want, not where it is
  • + Official MCP server plus LangChain/LlamaIndex/CrewAI integrations for direct agent use
  • + OpenAPI spec available; Python and JS SDKs are production-ready
Cons
  • - Free tier limited to 500 requests/month — tight for production agent workloads
  • - Rate limit docs are vague; concurrency limits vary by plan but exact RPM not clearly published
  • - Free tier is only 50 one-time credits — essentially a trial, not viable for ongoing agent use
  • - Credit costs vary by endpoint (2-30 credits/call) making usage prediction complex for agents
Badges
OpenAPI SpecAPI KeyFreemiumJSONBot Blocking: NoneNo CCweb-scrapingsearchcrawlingmarkdown-outputbatch-processingai-optimized
OpenAPI SpecAPI KeyFreemiumJSONBot Blocking: NoneNo CCweb-scrapingai-extractionmarkdown-outputcrawlingstructured-databrowser-automation

Olostep Integration

example.py
from olostep import Olostep
client = Olostep(api_key="your-api-key")result = client.scrapes.create(    url_to_scrape="https://example.com",    formats=["markdown"])print(result.result.markdown_content)

ScrapeGraphAI Integration

example.py
from scrapegraph_py import Client
client = Client(api_key="your-api-key")response = client.smartscraper(    website_url="https://example.com",    user_prompt="Extract the main heading and summary")print(response["result"])