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Riveter vs ScrapeGraphAI

Web Scraping

Riveter
Riveter
85
VS
ScrapeGraphAI
100
ScrapeGraphAI
Metric Riveter ScrapeGraphAI
Category Web Scraping Web Scraping
Pricing Freemium Freemium
Auth API Key API Key
Format JSON JSON
Bot Blocking None None
OpenAPI Spec No Yes
Credit Card Not required Not required
Rate Limit Not publicly documented 10 RPM (free), 30 RPM (starter), 60 RPM (growth), 200 RPM (pro)
Score Component Riveter ScrapeGraphAI
Base +50 +50
OpenAPI Spec 0 (No) +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 85 100
Riveter ScrapeGraphAI
Pros
  • + Single API replaces search + scraper + proxy + browser infra — agents make one call instead of orchestrating multiple tools
  • + Prompt-based config with structured output (custom enums, date formats, JSON schemas) means agents get predictable, typed responses
  • + Handles PDFs, images, and multi-page navigation autonomously — agents don't need separate tools for different content types
  • + 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
  • - No official Python or JS SDK and no public OpenAPI spec — agents must use raw HTTP and can't auto-generate tool definitions
  • - Rate limits and detailed paid pricing not publicly documented, making it hard to plan agent workload capacity
  • - 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
API KeyFreemiumJSONBot Blocking: NoneNo CCweb-scrapingsearchstructured-datadata-enrichmentai-agentspdf-extractionbatch-processing
OpenAPI SpecAPI KeyFreemiumJSONBot Blocking: NoneNo CCweb-scrapingai-extractionmarkdown-outputcrawlingstructured-databrowser-automation

Riveter Integration

example.py
import requests
response = requests.post(    "https://api.riveterhq.com/v1/search",    headers={        "Authorization": "Bearer YOUR_API_KEY",        "Content-Type": "application/json"    },    json={        "prompt": "Find the CEO and founding year",        "query": "Acme Corp",        "output_schema": {            "ceo": "string",            "founded": "integer"        }    })print(response.json())

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"])