TL;DR
ScrapeGraphAI is the better fit when you need to scrape any website and extract structured JSON or Markdown through an API. Mozenda is better when you want a visual scraper or a managed data-service vendor. ScrapeGraphAI starts at $20/month; Mozenda's first public paid plan is $500/month just for a pilot.
| Decision point | ScrapeGraphAI | Mozenda |
|---|---|---|
| Best fit | API-first web scraping, AI extraction, search, crawling, and monitoring | Visual scraping software and managed data services |
| Setup | Send a URL or query with a prompt and optional schema | Build agents in a web console or ask Mozenda to run the project |
| Public paid entry | $20/month Starter | $500/month Pilot |
| Output | Markdown, HTML, screenshots, links, images, branding, and structured JSON | CSV, TSV, XML, XLSX, JSON exports, and API-controlled collections |
| Integrations | Easy to ingest in apps, agents, RAG, n8n, dashboards, and data pipelines | Stronger when Mozenda owns the delivery workflow |
| Maintenance | Prompt and schema driven | Agent, XPath, support, or managed-service driven |
Bottom Line
ScrapeGraphAI and Mozenda are not the same kind of product.
ScrapeGraphAI turns web data into a programmable capability. You call an API, give it a URL or search query, describe the fields you need, and receive output your software can use immediately. That makes it a strong fit for AI agents, product backends, enrichment jobs, RAG pipelines, monitoring systems, dashboards, and internal data tools.
Mozenda is more traditional. Its public pages position it as web data extraction software plus managed data services. The software path is a point-and-click agent builder. The services path is closer to outsourced data collection: Mozenda helps build, maintain, clean, and deliver datasets.
That difference matters. If your team wants an API that can scrape any website and extract structured data, ScrapeGraphAI is the cleaner choice. If your team wants a vendor to operate the scraping workflow, Mozenda is worth evaluating.
Pricing Comparison
Pricing is the clearest difference in this comparison. ScrapeGraphAI has a free starting point and published self-serve plans. Mozenda has a 14-day Trial, then a much higher public paid entry point.
ScrapeGraphAI pricing:
| ScrapeGraphAI plan | Price | Credits | Notes |
|---|---|---|---|
| Free | $0 | 500 one-time credits | 10 requests/min |
| Starter | $20/month | 10,000 credits/month | 100 requests/min |
| Growth | $100/month | 100,000 credits/month | 500 requests/min |
| Pro | $500/month | 750,000 credits/month | 5,000 requests/min |
| Enterprise | Custom | Custom | Custom limits and infrastructure |
Yearly billing saves 15%. Credit packs are also available: 1,000 credits for $5, 10,000 credits for $40, and 50,000 credits for $150.
Mozenda pricing:
| Mozenda plan | Price | Included capacity | Notes |
|---|---|---|---|
| Trial | Free | 500 processing credits/month | 14 days, 1 user, 5 agents, 1 GB storage, 1 concurrent job |
| Pilot | $500/month | 5,000 processing credits/month | 1 user, 10 agents, 10 GB storage, 1 concurrent job |
| Enterprise | Quote-based | Custom | Multiple users, custom credits, custom agents, storage, and concurrency |
The public entry gap is hard to ignore: Mozenda's first paid plan costs 25x ScrapeGraphAI Starter. At the same $500/month spend, ScrapeGraphAI is on its Pro plan with 750,000 monthly API credits, while Mozenda is on its Pilot plan with 5,000 monthly processing credits.
Do not treat the credit units as identical. ScrapeGraphAI credits map to API services such as scrape, extract, search, crawl, and monitor. Mozenda processing credits belong to Mozenda's agent and harvesting model. The fair comparison is the buying motion: ScrapeGraphAI is cheaper to start and easier to scale before enterprise procurement; Mozenda can make sense if the price includes enough support or outsourced operations to replace internal work.
Why ScrapeGraphAI Shines
ScrapeGraphAI is strongest when web data needs to flow into software.
The core advantage is simple: the output is already developer-friendly. scrape can return Markdown, HTML, screenshots, links, images, branding, summaries, and JSON. extract returns structured JSON from prompts and optional schemas. search discovers sources before extraction. crawl handles async multi-page jobs. monitor handles recurring checks and change detection.
That means one platform can cover:
- Turning public pages into Markdown for LLM context.
- Extracting schema-ready JSON from product pages, directories, job boards, listings, or competitor pages.
- Searching the web and extracting from results.
- Crawling multiple pages without building a visual agent for every step.
- Monitoring prices, availability, content changes, or market signals.
For engineering teams, this is the important part: the extraction request can be defined by code at runtime. You do not need to prebuild a Mozenda agent every time the source, fields, or workflow changes.
from scrapegraph_py import ScrapeGraphAI
sgai = ScrapeGraphAI()
response = sgai.extract(
url="https://example.com/products",
prompt="Extract product names, prices, availability, and product URLs",
)That model is especially useful for products and AI systems where the target URL, schema, or research task changes dynamically.
Where Mozenda Fits
Mozenda still has a clear use case. It fits teams that want visual scraping software, support, or managed delivery more than they want a developer API.
Mozenda's public software page highlights point-and-click agent creation, templates, API access, agent grouping, scheduling, job sequencing, request blocking, premium harvesting, and support. Its services page goes further: Mozenda can handle implementation, recurring collection, cleaning, and delivery.
That can be useful when the buyer is an operations, sales, procurement, or research team that does not want to own scraper logic. In that case, the $500/month public entry price is not just paying for extraction. It may be paying for workflow ownership, support, and handoff.
But if your team has developers, wants direct API control, and needs structured output inside a product or pipeline, ScrapeGraphAI is the sharper fit.
API And Output Model
Mozenda's REST API is useful when you already use Mozenda agents. Its API docs describe operations for running agents, getting data, checking job progress, and exporting data. The docs also describe XML response objects.
ScrapeGraphAI's API is different. The API call defines the extraction task itself. You can pass a URL, prompt, and optional schema, then consume the result as structured data. That is a better model when the workflow lives in code.
The output difference also matters:
| Need | Better fit | Why |
|---|---|---|
| Structured JSON for an app | ScrapeGraphAI | Prompt plus schema returns usable API output |
| Markdown for an LLM or RAG pipeline | ScrapeGraphAI | Markdown is a first-class output |
| Dynamic extraction from changing URLs | ScrapeGraphAI | The task can be defined at request time |
| Visual agent setup | Mozenda | Point-and-click agent building is the product shape |
| Vendor-managed data collection | Mozenda | Managed services can own collection and delivery |
| Existing Mozenda agents | Mozenda | Its API can orchestrate those agents |
Integrations And Workflow Fit
ScrapeGraphAI integrates cleanly with almost any workflow because it outputs Markdown and structured JSON. Those are universal handoff formats.
That makes ScrapeGraphAI easy to connect to:
- n8n, Zapier, Make, and other automation builders.
- MCP clients, LangChain, LlamaIndex, CrewAI, and custom agentic workflows.
- RAG pipelines, vector databases, notebooks, BI tools, dashboards, and internal APIs.
- Product databases, enrichment pipelines, monitoring jobs, and backend services.
Mozenda can export common dataset formats and supports custom integrations, but it is more natural when the workflow is configured around Mozenda agents or Mozenda-managed delivery. ScrapeGraphAI is more natural when the workflow starts in code and the downstream system expects clean structured data.
Maintenance
Scraping maintenance is another point where ScrapeGraphAI stands out.
With ScrapeGraphAI, the main contract is the prompt and schema. If a page layout changes but still contains the same semantic information, extraction can often stay stable because the integration is not tied to one brittle CSS selector.
Mozenda's software path depends on agents. Its public software page mentions point-and-click setup and XPath procedures for more complex websites. That gives analysts visual control, but it can also create more workflow maintenance unless Mozenda is managing the job for you.
Verdict
Choose ScrapeGraphAI if you need:
- A lower-cost starting point than $500/month.
- An API to scrape websites and extract structured data.
- Markdown or structured JSON output.
- Search, crawl, scrape, extract, and monitor services in one platform.
- Easy ingestion into n8n, agentic workflows, RAG pipelines, apps, and data tools.
- A developer-first workflow where extraction tasks can change at runtime.
Choose Mozenda if you need:
- A visual scraping console for non-developers.
- A managed data-services relationship.
- Vendor help building and maintaining scraping projects.
- Existing Mozenda agents that need orchestration.
For developers, AI teams, and product engineers, ScrapeGraphAI is the stronger default. It is cheaper to start, easier to integrate, and better aligned with modern structured web data workflows.
Frequently Asked Questions
Is Mozenda cheaper than ScrapeGraphAI?
No, not at the public paid entry level. Mozenda's pricing page lists Pilot at $500/month after the 14-day Trial. ScrapeGraphAI starts with free credits and a $20/month Starter plan.
What happens at $500/month?
At $500/month, ScrapeGraphAI is on its Pro plan with 750,000 monthly API credits. Mozenda is on its Pilot plan with 5,000 monthly processing credits. The credit systems are different, but the public capacity positioning is very different.
Does Mozenda have an API?
Yes. Mozenda has a REST API for controlling agents, jobs, data collections, and exports. It is best understood as an API around Mozenda objects. ScrapeGraphAI is different because the API call can define the extraction task directly.
Does ScrapeGraphAI replace Mozenda agents?
For many developer workflows, yes. A ScrapeGraphAI extract call can replace a field extraction agent when the goal is structured JSON from a page. For visual workflows or vendor-managed delivery, Mozenda may still fit.
Which tool is better for AI agents?
ScrapeGraphAI is the stronger fit for AI agents because it exposes direct services for scraping, extraction, search, crawling, and monitoring, then returns Markdown or structured JSON that agent workflows can ingest.
Can ScrapeGraphAI integrate with n8n or agentic workflows?
Yes. ScrapeGraphAI outputs Markdown and structured JSON, so teams can ingest results in n8n, Zapier, Make, MCP clients, LangChain, LlamaIndex, CrewAI, custom agents, RAG systems, databases, and dashboards.