ScrapeGraphAI Review

ScrapeGraphAI is an LLM-powered web scraping API and suite that extracts structured data from websites using natural language prompts.

shipped Jul 3, 2026codepaid

Domain rating51Monthly visits2.1K/mo

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Why it matters

1Offers a Free Plan at $0 with 500 API credits.

2SOC 2 Type 2 Compliant, ensuring data security and privacy.

3Leverages graph-based AI for selector-free web scraping.

4Provides an open-source Python library for developers.

Stork Quadrant

Becomes the API· 25/100

Replaceable as a UI, but kept alive as the API the agents call.

“ScrapeGraphAI is a thin wrapper around LLM capabilities that any builder can replicate in minutes with Claude or GPT-4 directly. The core promise—use an LLM to read a webpage and extract data—is not defensible because the LLM is doing the work, not the tool. Once agents can call browsers natively, this product evaporates.”
— Claude Haiku 4.5, scored 2026-07-08

Defensibility · 0/100

Physical-world coupling
Regulatory moat
Network liquidity
Proprietary refreshing data
High-trust catastrophic workflows
Multi-party coordination
Brand / community / taste

An LLM alone could replace

Extract structured data from a static or semi-dynamic webpage using natural language instructions
Convert unstructured HTML into JSON or CSV format via LLM interpretation
Handle selector-free scraping by having an LLM read and parse page content
Generate scraping logic on-the-fly without pre-built templates or rules

Agent-Readiness · 55/100

Verified MCP
Listed on agent surfaces
Usage-based pricing— pricing page heuristic match: https://scrapegraphai.com/pricing
Headless agent auth— https://docs.scrapegraphai.com/introduction (api-key auth)
Public OpenAPI— https://docs.scrapegraphai.com/introduction
Active changelog— https://scrapegraphai.com/blog/scrapegraphai-v2 (2026-04-22)
llms.txt— https://scrapegraphai.com/llms.txt

How to defend

Pivot to a data moat: build a refreshing index of scraped data (pricing, inventory, job listings, real estate) that updates hourly and becomes the source of truth. Or become the orchestration layer for multi-step scraping workflows where you handle retries, rate limiting, and structured output validation at scale—moving from UI to infrastructure.

Ship an MCP server and list it on Stork — biggest single point gain (+25).
Get listed in the Anthropic MCP registry, Cursor, or Claude Desktop (+20).

How this score is computed →See the full quadrant How to defend

About ScrapeGraphAI

Business Model

Subscription SaaS

Free Credits

500 API credits

Founded

2022

Funding

Seed

Platforms

Web, API

Target Audience

Individuals, startups, and teams needing web data extraction services.

Pricing Plans

Free Plan

$0 / monthly

• 500 API credits, one-time
• 10 requests/min
• 1 monitor
• 1 concurrent crawl

Starter Plan

$20/mo

• 10,000 API credits per month
• 100 requests/min
• 5 monitors
• 3 concurrent crawls

Growth Plan

$100/mo

• 100,000 API credits per month
• 500 requests/min
• 25 monitors
• 15 concurrent crawls

Pro Plan

$500/mo

• 750,000 API credits per month
• 5,000 requests/min
• 100 monitors
• 50 concurrent crawls

Enterprise

Custom / custom billing

• Ad-hoc credits
• Custom rate limits
• Dedicated support
• SLA guarantee

API Docs GitHubOpen Source

Specs

API Docs

View Documentation →

GitHub

View Repository →

API Available

Yes, public API

Screenshots

overview

What is ScrapeGraphAI?

ScrapeGraphAI is an AI-powered web scraping tool that enables AI developers, data analysts, and businesses to extract structured data from websites, HTML content, and local documents using natural language prompts. It leverages graph-based AI for intelligent, selector-free web scraping tailored to dynamic content extraction, eliminating the need for traditional CSS selectors or XPath queries.

features

Key Features of ScrapeGraphAI

ScrapeGraphAI provides a comprehensive set of features designed for efficient and adaptable web data extraction, utilizing AI to streamline the process and reduce manual intervention.

AI-Powered Extraction: Extracts structured data using natural language prompts and optional schemas.
Zero Maintenance: Automatically adapts to website layout changes, reducing ongoing maintenance.
Automatic Proxy Management: Handles proxy rotation and management for reliable scraping.
JavaScript Rendering: Capable of rendering JavaScript-heavy websites for complete data access.
Auto-Adapts to Changes: Graph-based AI architecture automatically adjusts to website structural modifications.
Built-in Rate Limiting: Manages request rates to avoid IP blocks and ensure compliance.
Cloud-Ready API: Offers a scalable API for integration into various applications.
AI-Agent Ready: Designed to feed structured web data directly into AI agents for enhanced decision-making.
Enterprise Support: Provides dedicated support for large-scale deployments and custom requirements.

use cases

Who Should Use ScrapeGraphAI?

ScrapeGraphAI is designed for a range of technical and business users who require efficient, automated web data extraction without the complexities of traditional scraping methods.

AI Developers: For building datasets for machine learning and AI training, and feeding AI agents with structured web data.
Data Analysts and Researchers: For collecting research data, conducting market analysis, and aggregating content.
Businesses: For e-commerce data extraction, product price tracking, competitive intelligence, and lead generation.
Developers Building Scraping-Powered Platforms: For integrating robust, AI-driven scraping capabilities into their applications.
Individuals Automating Data Collection: For personal projects requiring automated web data retrieval.

how to use

How to Use ScrapeGraphAI

Getting started with ScrapeGraphAI involves utilizing its API or open-source Python library to define extraction tasks using natural language prompts and schemas.

1Sign up for a ScrapeGraphAI account and obtain an API key.
2Install the ScrapeGraphAI Python library via pip.
3Define the target URL and the desired data structure using natural language prompts or a JSON schema.
4Execute the scraping task via the API or Python SDK.
5Receive structured data output in formats such as JSON, Markdown, or HTML.

pricing

ScrapeGraphAI Pricing & Plans

ScrapeGraphAI offers a tiered pricing model, including a free plan and several paid subscription options, designed to accommodate various usage levels from individual developers to large enterprises. All plans include access to the API, automatic proxy management, JavaScript rendering, and AI-powered extraction.

Free Plan: $0 per month, includes 500 API credits.
Starter Plan: $20 per month, provides increased API credits and features.
Growth Plan: $100 per month, offers expanded capabilities for growing needs.
Pro Plan: $500 per month, designed for professional and high-volume users.
Enterprise: Custom pricing, tailored for large organizations with specific requirements and dedicated support.

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Pros

+AI-powered, natural language prompt-based extraction eliminates the need for complex CSS/XPath selectors.
+Graph-based AI architecture provides self-adapting capabilities to website layout changes, reducing maintenance.
+Includes automatic proxy management, JavaScript rendering, and built-in rate limiting for robust scraping.
+Offers an open-source Python library and a cloud-ready API for flexible integration.
+SOC 2 Type 2 Compliant, ensuring adherence to security and privacy standards.
+Provides a Free Plan with 500 API credits, allowing users to test functionality.

Cons

−Requires Python knowledge and understanding of API keys and JSON output, making it less accessible for non-technical users.
−Some users have reported inconsistencies between the UI Web Playground and API results, requiring prompt adjustments.
−Feedback indicates occasional issues with consistency and communication from founders.
−Lacks features like bulk CSV uploads and downloads, which some users desire for workflow efficiency.
−Training on user data is 'always' for free plans as a condition of use, which may be a concern for some users.

Policies

Pricing Page

View Pricing→

Similar Tools

ScrapeGraphAI vs Competitors

ScrapeGraphAI distinguishes itself in the web scraping market through its AI-powered, natural language processing capabilities and graph-based architecture, offering an alternative to traditional selector-based tools and other AI-driven scrapers.

LLM Scraper↗

This TypeScript library converts any webpage into structured data using LLMs, leveraging function calling for precise extraction.

LLM Scraper is a TypeScript library, which means a different programming ecosystem compared to ScrapeGraphAI's Python. It focuses on direct structured data conversion via LLMs, while ScrapeGraphAI emphasizes a graph-based pipeline for complex scraping logic.

Firecrawl (Open-source library)On Stork

Firecrawl offers an open-source Python library that uses AI to convert URLs into clean, LLM-ready markdown or structured JSON, adapting to website changes automatically.

While Firecrawl also offers a paid API, its open-source Python library provides similar AI-powered, selector-free extraction to ScrapeGraphAI. The trade-off is that ScrapeGraphAI's graph-based approach might offer more granular control over complex scraping flows, whereas Firecrawl's library is more focused on direct content and structured data output.

Scraping-AI↗

Its Python SDK provides an LLM-driven semantic extraction engine that transforms raw webpages into validated JSON without relying on fragile DOM selectors.

Scraping-AI offers a Python SDK for LLM-driven semantic extraction, similar to ScrapeGraphAI's core functionality. The main difference is its pricing model, offering a free trial before requiring payment, unlike ScrapeGraphAI which is an open-source library with costs primarily for LLM API calls.