Apify
A cloud platform for running thousands of ready-made scrapers, plus the infrastructure to build your own
Apify is a cloud platform for web scraping and browser automation. Its unit of work is an Actor, a serverless program that runs in the cloud and returns structured data; Apify Store lists tens of thousands of ready-made Actors for sites like Google Maps, LinkedIn, Instagram, Amazon, and TikTok, and developers can publish their own. The platform supplies the surrounding infrastructure that scraping actually requires: rotating proxies, headless browsers, dataset storage, schedules, an API, webhooks, and a hosted MCP server that lets AI agents call any Actor as a tool. It starts free with $5 of monthly platform credit and is metered by compute rather than by seat.
Overview
Most go-to-market teams reach a point where the data they need does not exist in any vendor's database: a list of every dentist in three counties with a website and no online booking, every Shopify store running a specific app, every job posting mentioning a competitor. The answer is scraping, and the reason scraping projects fail is almost never the parsing logic. It is the infrastructure around it: proxies that stop getting blocked, headless browsers that survive anti-bot checks, retries, storage, scheduling, and somewhere to put the output. Apify sells that infrastructure and, on top of it, a marketplace of scrapers other people have already debugged.
The platform is organized around Actors. An Actor is a containerized program with a defined input schema and a dataset output, run on demand, on a schedule, or via API. Apify Store carries tens of thousands of them, the great majority built by third-party developers who monetize their work through the platform. For a non-engineer, the practical workflow is closer to buying software than writing it: find the Google Maps Scraper, fill in a search term and a location, run it, and export a CSV. For an engineer, the same platform is a deployment target for custom code written with Crawlee, Apify's open-source crawling library for JavaScript and Python, which runs locally or anywhere else and is not locked to the platform.
Since 2024 the company has aimed the whole thing at AI agents. The hosted MCP server exposes Store Actors as callable tools to Claude, ChatGPT, Cursor, and anything else speaking Model Context Protocol, which turns a scraper into something an agent can invoke mid-conversation. Apify now describes itself as a marketplace of tools for AI rather than a scraping company, and has added agent-oriented plumbing including per-request payment protocols and connectors that let an Actor act on a logged-in service without seeing the credentials.
The trade-off buyers should understand before signing up is the billing model. Apify charges for compute, and the meter is memory multiplied by time, so an identical scrape costs more if the Actor requests more RAM or runs longer against a slow site. On top of that, many Store Actors carry their own per-result or per-event fee set by their developer. The result is a bill that is genuinely hard to forecast on the first month and quite predictable by the third, once you have measured what your specific jobs cost.
Best for
Growth, RevOps, and data teams that need custom web data at a scale a manual list build cannot reach, and that want ready-made scrapers for the common sources with an escape hatch into custom code when a target is unusual. Also strong for anyone wiring web data into an AI agent through MCP.
Not the right fit for
- Teams that want a fixed monthly bill; compute metering plus per-Actor fees means the invoice moves with what you run.
- Non-technical buyers who need a single point-and-click recorder for arbitrary sites; that is closer to what Browse AI and Octoparse sell, and Apify's equivalent is a general-purpose crawler with a real configuration surface.
- Buyers who want the contact data itself rather than the means to collect it; a B2B database is a different purchase from a scraping platform.
- Organizations whose legal position forbids collecting data from sites whose terms prohibit automated access, which is a policy question the tool cannot settle for you.
- Anyone expecting the Store to be uniformly maintained; quality across tens of thousands of third-party Actors is genuinely uneven and some are abandoned.
How it works
- 1
You create an account and land in the Apify Console. From there the fastest path is Apify Store: search for the site you want data from, open the Actor, read its input schema, and run it. Input is a form generated from the Actor's schema, so a Google Maps job asks for search terms, location, and maximum results rather than for code.
- 2
The run executes in a container on Apify's infrastructure with an amount of memory you choose, which also determines CPU share. Output lands in a Dataset, a tabular store you can preview in the browser and export as JSON, CSV, Excel, XML, or RSS, or read through the API. Files and screenshots go to a Key-Value Store; queued URLs live in a Request Queue.
- 3
Blocking is handled by Apify Proxy. Datacenter IPs are included on every plan and are cheap; residential IPs are billed by the gigabyte and are what you switch to when a target site starts refusing datacenter traffic. There is also a SERP proxy priced per thousand search result pages. Most Store Actors accept a proxy configuration in their input, so switching proxy type is a setting rather than a rewrite.
- 4
Scheduling and integration turn a one-off run into a pipeline. Schedules use cron expressions; webhooks fire on run completion or failure; native integrations push results into Google Sheets, Slack, Airtable, Zapier, Make, n8n, Google Drive, and cloud storage buckets. The REST API and the official JavaScript and Python clients cover everything the Console can do, including starting runs and paging through datasets.
- 5
For custom work, you write an Actor locally with the Apify CLI and Crawlee, test it on your machine, and push it. Apify builds the Docker image, hosts it, and gives it the same input schema, storage, proxy, and scheduling surface as any Store Actor. If you want to sell it, you publish it to Store and choose a monetization model: pay per event, pay per usage, or a monthly rental.
Feature breakdown
28 features in 5 modulesApify Store
The marketplace of ready-made scrapers, which is why most people arrive.- Tens of thousands of published Actors
- Ready-to-run scrapers and automations covering search engines, maps, social platforms, marketplaces, job boards, travel sites, and app stores, the great majority built and maintained by third-party developers.
- Form-based input schemas
- Every Actor declares its inputs, so the Console renders a real form (search terms, URLs, limits, proxy settings) instead of asking for a JSON blob, though JSON editing is available.
- Free trials on rented Actors
- Paid Store Actors typically offer a limited trial so you can confirm the output shape matches what you need before committing to the monthly rental or per-result fee.
- Public run history and ratings
- Actor pages show recent success rates, last modified date, user counts, and reviews, which is the main defence against picking an abandoned scraper.
- Store discounts by plan
- Paid plans carry Bronze, Silver, and Gold discount levels applied to rented Actor fees, so heavier accounts pay less per Actor.
Runtime and infrastructure
The parts that make a scraper survive contact with a real website.- Serverless Actor runs
- Containerized jobs with memory selectable in powers of two from 128 MB to 32 GB; memory also sets CPU share and disk, so it is the main performance and cost lever.
- Apify Proxy
- Datacenter IPs included with every plan, residential IPs billed per gigabyte with country targeting and session persistence, and a SERP proxy priced per thousand result pages.
- Headless browser support
- Playwright and Puppeteer run natively with browser fingerprint handling, which is what gets past sites that will not serve content to a plain HTTP client.
- Datasets, Key-Value Stores, and Request Queues
- Three purpose-built storage types: tabular results, arbitrary files and screenshots, and deduplicated URL queues that let a crawl resume rather than restart.
- Concurrency and resource limits by plan
- Each plan caps simultaneous runs and total memory across the account, from a modest ceiling on Free up to several hundred concurrent runs on Business.
- Automatic retries and run logs
- Failed requests retry with backoff and every run keeps a streamed log, which is where you actually diagnose a scraper that stopped returning rows overnight.
Building and publishing
The developer half: write your own Actor, deploy it, and optionally sell it.- Crawlee
- Apify's open-source crawling library for JavaScript and Python, handling queues, concurrency, proxy rotation, and session management; it runs locally or on any cloud, not just Apify.
- Apify CLI and local development
- Scaffold from a template, run and debug the Actor on your own machine against local storage, then push to build and deploy as a Docker image.
- Actor templates
- Starter projects for JavaScript, TypeScript, Python, Playwright, Puppeteer, Cheerio, Scrapy, and LangChain-style agent patterns, with the creation flow steering you to a relevant one.
- Input schema and output views
- A JSON schema file generates the input form, validation, and API contract, and output views control how the dataset is presented to users of your Actor.
- Monetization models
- Publishers choose pay per event (charge on a defined action such as a returned result), pay per usage (users pay only platform compute), or a fixed monthly rental, with Apify handling billing and payouts.
- File upload into Actor input
- Actors can accept uploaded files such as CSV, JSON, or PDF directly as input, stored in a key-value store, which removes the need to host a seed list somewhere public.
Automation, API, and AI
Getting data out on a schedule, into other tools, and into agents.- Schedules
- Cron-based recurring runs with per-schedule input overrides, so the same Actor can serve daily monitoring and a monthly full refresh from one definition.
- REST API and official clients
- Full API coverage for starting runs, polling status, and paging datasets, with maintained JavaScript and Python clients and synchronous run-and-return endpoints for short jobs.
- Webhooks
- Fire on run success, failure, timeout, or Actor build events, with a payload containing the run and dataset identifiers so a downstream service can collect results immediately.
- Hosted MCP server
- A Model Context Protocol endpoint that exposes Store Actors, datasets, and run management as tools for Claude, ChatGPT, Cursor, and other MCP clients, so an agent can discover and run a scraper mid-task.
- Native integrations
- Direct connectors for Google Sheets, Google Drive, Slack, Airtable, Zapier, Make, n8n, GitHub, Gmail, and cloud storage, plus dataset push into vector stores such as Pinecone and Qdrant.
- Agent payment and connector plumbing
- Support for per-request agent payment over the x402 protocol on eligible Actors, and MCP connectors that let an Actor act on a logged-in service through a proxy without the Actor seeing credentials.
Operations and governance
Account-level controls for teams running scrapers continuously.- Organization accounts and roles
- Shared organization workspaces with per-member permissions on Actors, storages, and billing, so an agency can separate client work from its own.
- Usage dashboard
- Console breakdown of compute units, proxy gigabytes, storage operations, and rented Actor fees, which is the only reliable way to understand a surprising invoice.
- Spending limits and alerts
- Configurable caps and notifications on account usage, worth setting on day one given how quickly a misconfigured crawl can consume credit.
- Data retention windows
- Datasets and stores age out automatically after a plan-dependent window, so anything you need permanently should be exported or pushed to your own storage.
- Standby Actors
- Actors can be kept warm behind an HTTP endpoint for low-latency request-response use, which is what makes them usable as live tools rather than batch jobs.
Use cases
5 documentedGrowth lead building a local services prospect list
The target segment is independent HVAC contractors in twelve metro areas, and no B2B database covers them well because most have no LinkedIn presence and inconsistent firmographics.
A Google Maps Actor scheduled across the twelve areas returns name, address, phone, website, rating, and review count; a second run checks each website for a booking widget, and the list that reaches the SDR team is segmented by whether the prospect already has the thing being sold.
Ecommerce operator monitoring competitor pricing
Six competitors change prices irregularly and the team currently checks by hand once a week, which is both expensive and too slow to react to promotions.
A daily scheduled Actor writes each competitor's catalogue into a dataset, a webhook pushes the diff into Slack, and repricing decisions move from weekly guesswork to a morning alert on the twenty SKUs that actually changed.
Agency running research for multiple clients
Each client wants a different data pull, none large enough to justify building and maintaining bespoke scrapers, and the agency does not want to own proxy infrastructure.
Store Actors cover most requests with an afternoon of configuration, organization accounts keep client work separated, and the compute cost per project is small enough to bill through as a line item rather than absorb as overhead.
Engineer wiring web data into an AI agent
An internal research agent needs live web data, and hand-rolling a scraper plus proxy pool for every new source is the bottleneck.
Connecting the agent to Apify's MCP server makes thousands of Store Actors available as callable tools, so adding a new data source becomes selecting an Actor rather than shipping code, with runs and costs visible in one console.
Developer publishing a niche scraper
A working scraper for an industry-specific directory has value beyond the team that built it, but billing, hosting, and support would be a project of their own.
Publishing it to Apify Store with a pay-per-event price puts it in front of the platform's user base, with Apify handling runtime, proxies, invoicing, and payouts, and the developer keeping the code.
Pricing
from Free with $5 of monthly platform credit; paid plans from $29 per month ($26 billed annually)Prepaid platform credit with usage metered against it. Each plan includes a monthly credit allowance equal to its price, consumed by compute units (memory multiplied by run time), proxy bandwidth, storage operations, and data transfer. Rented or paid Store Actors carry their own fees on top, set by the Actor's developer as a monthly rental, a per-event charge, or a per-result charge. Seats are not the pricing axis; usage is.
| Plan | Price | Includes |
|---|---|---|
| Free | $0 per month |
Genuinely enough to evaluate the platform and to run small recurring jobs, which is unusual in this category. |
| Starter | $29 per month ($26 billed annually) |
The tier most small teams land on, and the point at which overage above the included credit is charged rather than blocked. |
| Scale | $199 per month ($179 billed annually) |
|
| Business | $999 per month ($899 billed annually) |
Custom enterprise arrangements exist above this for volume commitments, SLAs, and procurement requirements. |
Add-ons
- Residential proxy (About $8 per GB on Free and Starter, falling to about $7 on Business): The cost that surprises people; a browser-based scrape of an image-heavy site burns bandwidth fast unless you block asset loading.
- Datacenter proxy (30 IPs included on Starter, then about $1 per IP; cheaper per IP on higher plans): Free and cheap, and blocked by an increasing share of well-defended targets.
- SERP proxy (About $2.50 per 1,000 search result pages, falling to about $1.70 on Business)
- Rented Store Actors (Set by each Actor's developer, commonly a monthly rental or a per-result fee): This is a separate line from platform credit and is where a nominally $29 account becomes a $120 account.
Billing notes
- Included platform credit does not roll over; if you pay $199 for Scale and consume $120 of usage, the remaining $79 expires at the end of the cycle.
- A compute unit is one gigabyte of Actor memory for one hour, so allocating more RAM than an Actor needs directly multiplies the bill for no benefit.
- Paid Store Actors bill separately from platform usage, which is the single most common reason a first invoice is larger than expected.
- On the free plan, exhausting credit blocks further runs; on paid plans usage above the included credit is charged as overage, so spending limits are worth configuring immediately.
- Annual billing is about ten percent cheaper on every paid tier as published August 2026.
- Proxy bandwidth, storage operations, and data transfer are metered alongside compute, so a job that returns few rows can still be expensive if it loaded a lot of pages.
Value assessment: Judged against building the same thing yourself, Apify is inexpensive: a residential proxy pool, headless browser fleet, retry logic, and storage would cost more than $29 a month in engineering attention alone, before any infrastructure. Judged against a fixed-price scraping tool, it is harder to compare, because you are buying capacity rather than a defined output, and the honest answer for month one is that you cannot forecast the bill precisely. The mitigation is straightforward: run the job once at a small limit, read the usage breakdown, multiply. Teams that do this usually find the real cost of a recurring list build lands in the tens of dollars a month, and teams that skip it are the ones who write reviews about unpredictable pricing.
Strengths & limitations
Strengths
- The Store is the moat: for most common data sources, someone has already built, debugged, and now maintains the scraper, which collapses a two-week project into an afternoon of configuration.
- Real infrastructure underneath, with proxies, headless browsers, storage, scheduling, and retries handled rather than left as an exercise.
- Genuinely usable free tier with $5 of monthly credit, no credit card, and full API and MCP access, so evaluation costs nothing.
- Crawlee is open source and runs anywhere, which meaningfully limits lock-in for teams writing their own crawlers.
- The hosted MCP server is one of the better-executed AI integrations in this category, turning thousands of scrapers into agent-callable tools without custom glue.
- Consistently high user ratings across G2, Capterra, and Trustpilot, with documentation and developer experience singled out as reasons.
- A publishing and monetization path that gives developers a reason to keep Actors current, which is why the catalogue stays broad.
Limitations
- Compute-unit billing is hard to predict before you run a job, because cost is memory multiplied by time and both depend on how the target site behaves that day.
- Included platform credit expires monthly with no rollover, so buying a tier for occasional heavy months means paying for unused capacity in the quiet ones.
- Store Actor quality is uneven; some are abandoned, some break silently when a target site changes markup, and the run-success statistics on the Actor page are the only pre-purchase signal.
- Paid Actors add a second billing layer on top of platform credit, and the total cost of a workflow is not visible from any single number on the pricing page.
- Residential proxy bandwidth is charged by the gigabyte and is easy to waste, since a headless browser loads images, fonts, and trackers unless the Actor is configured to block them.
- Building a custom Actor requires real JavaScript or Python skill; the platform is not a no-code recorder and does not pretend to be.
- Datasets age out on a plan-dependent retention window, so anything of lasting value has to be exported or pushed into your own storage.
- Scraping some sources carries legal and terms-of-service exposure the platform cannot remove, and the responsibility for what you collect stays with you.
Head-to-head comparisons
6 alternativesApify vs Browse AI
from Free (50 credits per month, 2 websites); paid plans from $19 per month billed annuallyDifferent buyers. Browse AI is a point-and-click recorder aimed at people who will never open a terminal: you demonstrate the extraction in a browser, it monitors the page and alerts you on change, and pricing is a predictable monthly credit bundle. Apify assumes more technical comfort and gives far more in return: a marketplace of maintained scrapers, real proxy infrastructure, custom code deployment, and an API that a pipeline can be built on. Pick Browse AI for a handful of pages watched by a marketer; pick Apify when the job is thousands of pages, an unusual target, or feeding a system rather than a spreadsheet.
Full Apify vs Browse AI comparisonApify vs Firecrawl
from Free (1,000 credits per month); paid plans from about $16 per month billed annually (about $19 billed monthly)Firecrawl is narrower and cleaner: point it at a URL or a domain and get back markdown or structured JSON suited to feeding an LLM, with a simple API and simple credit pricing. Apify is a general-purpose platform, and its advantage shows up when the target is a specific application rather than a content site, since a Google Maps or Instagram Actor already handles pagination, authentication quirks, and rate limits that a generic crawler will not. Many teams use both: Firecrawl for turning documentation and marketing sites into agent context, Apify for structured extraction from named platforms.
Full Apify vs Firecrawl comparisonApify vs Octoparse
from Free for 10 tasks and 50,000 exported rows per month; paid plans from $58 per month billed annually ($69 monthly)Octoparse is the desktop-first visual scraper: build the extraction by clicking through a page in its own browser, run locally or in its cloud, on a fixed monthly plan. That predictability is its real selling point against Apify's usage meter. Apify wins on scale, on infrastructure quality, on the breadth of ready-made Actors, and on being programmable end to end. If nobody on the team writes code and the volumes are modest, Octoparse is the easier purchase; if scraping is becoming a system rather than a task, Apify is the one that keeps working.
Full Apify vs Octoparse comparisonApify vs PhantomBuster
from $69 per month (Start), or $56 per month billed annuallyOverlapping on social platforms and different everywhere else. PhantomBuster is purpose-built for LinkedIn, Instagram, and similar networks, with session-cookie handling, sensible daily limits, and sequenced workflows aimed squarely at outbound teams. Apify covers those platforms too, through Store Actors of varying quality, and covers everything else besides. A GTM team whose entire need is LinkedIn automation will find PhantomBuster more opinionated and less fiddly; a team scraping maps, marketplaces, job boards, and LinkedIn will not want four vendors.
Full Apify vs PhantomBuster comparisonApify vs Clay
from Free plan; paid from $149/moComplementary rather than competing, though the boundary blurs. Clay is a spreadsheet-shaped enrichment environment that fans a list of companies or people out across dozens of data providers and AI prompts; Apify is where the raw list comes from when no provider has it. The common pattern is an Apify Actor producing a scraped source list, pushed into Clay for enrichment, scoring, and CRM sync. Clay does include a scraping capability, so light needs can stay in one tool, but sustained crawling at volume is cheaper and more controllable on Apify.
Full Apify vs Clay comparisonApify vs n8n
from About $24/mo (Cloud Starter, 2,500 executions; roughly $20 on annual billing)These sit at different layers and are frequently used together. n8n is the workflow orchestrator, the thing that decides what runs when and where the output goes; Apify is the extraction engine it calls. n8n's own HTTP nodes can scrape simple pages, but it has no proxy pool, no headless browser fleet, and no library of maintained scrapers, so anything defended will fail there. The durable setup is an n8n workflow that triggers an Apify Actor, waits on the webhook, and routes the dataset into a CRM or warehouse.
Full Apify vs n8n comparisonImplementation & onboarding
- Setup time
- Minutes for a first Store Actor run: sign up, pick an Actor, fill the form, export a CSV. A scheduled pipeline with proxy configuration, webhooks, and a downstream destination is a half day. A custom Actor is a normal software project, measured in days, and its length depends on how hard the target defends itself rather than on Apify.
- Learning curve
- Low to run existing Actors, moderate to operate the platform well. The two things that take time are understanding the cost model well enough to predict a bill, and learning which proxy and browser settings a given target requires. Writing Actors requires working JavaScript or Python.
- Onboarding
- Fully self-serve with extensive documentation, the free Apify Academy course series on web scraping, template projects, and an active Discord. Business plans include an account manager; below that, support is chat and community.
- Migration notes
- There is little vendor data to migrate, since scraped datasets are yours and export as JSON, CSV, or Excel through the API. Custom crawlers built on Crawlee are portable by design and can run on your own infrastructure. What does not port is anything specific to Store Actors you rented, so replacing them means finding or building equivalents. Export datasets you care about before cancelling, because retention windows delete them on a schedule.
Platform, API & security
- Platforms
- Web consoleREST APIJavaScript and Python API clientsApify CLIDocker-based Actor runtimeHosted MCP server
- API
- Comprehensive REST API covering Actor runs, builds, datasets, key-value stores, request queues, schedules, and webhooks, with official JavaScript and Python clients, synchronous run-and-get-results endpoints for short jobs, and an OpenAPI specification. Standby Actors expose a persistent HTTP endpoint for low-latency request-response use.
- Compliance
- GDPRSOC 2 Type IICCPA
- Data residency
- Platform operated from the EU with the company headquartered in Prague; compute runs on cloud infrastructure with storage regions tied to the platform rather than customer-selectable.
- SSO
- Single sign-on and organization-level access controls available on higher plans and enterprise arrangements.
- Security notes
- API tokens are scoped and revocable, organization accounts separate member permissions across Actors and storages, and MCP connectors are designed so an Actor acts through a credential proxy rather than receiving the credentials themselves. Because scraped data can include personal data, the controller obligations under GDPR, lawful basis, retention, and subject rights, remain the customer's.
Support & resources
- Channels
- Chat support on paid plansEmailDiscord communityDedicated account manager on Business
- Documentation
- One of the stronger documentation sets in this category, covering the platform, the SDKs, Crawlee, and Actor publishing, plus Apify Academy, a free course series on web scraping and anti-blocking that is widely used as general education on the topic.
- Community
- An active Discord with Apify engineers present, a large body of open-source repositories, and a developer community that exists partly because publishing Actors is a revenue channel rather than a hobby.
Company
- Founded
- 2015
- Headquarters
- Prague, Czech Republic
- Ownership
- Independent, venture-backed
- Founders
- Jan Curn, Jakub Balada
- Employees
- ~100 (est. 2026)
- Funding
- Roughly $5 million raised in total, including a EUR 2.8 million round in 2024 led by J&T Ventures with participation from Reflex Capital; the company has reported profitability on revenue in the high single-digit millions of euros.
Funding history
| Round | Amount | Year | Notes |
|---|---|---|---|
| Y Combinator Fellowship | Not disclosed | 2015 | Founded out of the YC Fellowship program in Mountain View before relocating to Prague. |
| Seed | Not disclosed | 2016 | Raised after moving operations to Prague. |
| Growth round | EUR 2.8 million | 2024 | Led by J&T Ventures with existing investor Reflex Capital participating. |
Timeline
- 2015Founded by Jan Curn and Jakub Balada out of the Y Combinator Fellowship, focused on making web crawlers accessible through JavaScript and headless browsers.
- 2016Relocates to Prague, raises seed funding, and expands from a crawler product into a full scraping and browser automation platform.
- 2019Apify Store opens to third-party developers, turning the platform into a marketplace rather than a hosting service.
- 2022Crawlee released as the successor to the Apify SDK, an open-source crawling library for Node.js that runs anywhere, later joined by a Python version.
- 2024Raises EUR 2.8 million led by J&T Ventures; Actor monetization models expand and the catalogue grows into the tens of thousands.
- 2025Hosted MCP server launches, exposing Store Actors as tools to Claude, ChatGPT, Cursor, and other MCP clients.
- 2026Repositions as a marketplace of tools for AI agents, adding per-request agent payments over the x402 protocol, MCP connectors for logged-in services, and file upload into Actor inputs.
Integrations
- Google Sheets
- Google Drive
- Slack
- Airtable
- Zapier
- Make
- n8n
- GitHub
- Gmail
- Amazon S3
- Pinecone
- Qdrant
- LangChain
- Model Context Protocol clients
- Webhooks and REST API
Frequently asked questions
12 questionsWhat is Apify used for?
Collecting structured data from websites at scale, and running browser automation in the cloud. The most common jobs are lead and prospect list building from directories and maps, competitor and price monitoring, social media and review scraping, SEO and SERP data collection, and feeding live web data into AI agents and RAG pipelines. You either run a ready-made scraper from Apify Store or deploy your own code as an Actor.
Is Apify free?
There is a permanent free plan with $5 of platform credit each month and no credit card required, which includes full access to Apify Store, the API, and the MCP server. When the credit runs out, runs stop rather than generating a bill. Paid plans start at $29 per month, or $26 billed annually, and that price is itself an amount of usage credit rather than a licence fee.
How does Apify pricing actually work?
Two layers. The first is platform usage, metered in compute units, where one compute unit is one gigabyte of Actor memory running for one hour, plus proxy bandwidth, storage operations, and data transfer. Your monthly plan price is a prepaid credit against that usage, and it does not roll over. The second layer is Store Actors that charge their own fee, either a monthly rental or a per-result or per-event price set by the developer. The second layer is what makes first invoices surprising.
What is an Apify Actor?
A serverless cloud program with a defined input schema and a dataset output. In practice it is a scraper or automation packaged so that anyone can run it from a form, on a schedule, or through the API without knowing how it was built. Actors run in Docker containers on Apify's infrastructure, and any developer can publish one to Apify Store and charge for it.
Do I need to know how to code to use Apify?
No, to run existing Actors. Store Actors present a form: you type a search term or paste URLs, choose a result limit, and run. Yes, if you need something the Store does not cover, since building a custom Actor means writing JavaScript or Python. Apify is not a visual point-and-click recorder, which is the main structural difference from tools like Browse AI and Octoparse.
How much does it cost to scrape 10,000 results on Apify?
It depends on the Actor and the site, which is the honest answer, but the method is reliable: run the job once with a limit of a hundred results, open the usage breakdown for that run, and multiply. For a typical directory or maps scrape, ten thousand results usually lands in the single-digit to low-double-digit dollars of platform usage, plus whatever per-result fee the Actor charges. Browser-heavy targets behind residential proxies cost considerably more.
Is web scraping with Apify legal?
The platform is a tool and the legality depends on what you collect, from where, and how you use it. Collecting publicly available factual data is treated differently in most jurisdictions from collecting personal data, bypassing authentication, or ignoring a site's terms of service. If you scrape personal data about EU residents you are a controller under GDPR with all that implies. Apify publishes guidance on ethical scraping, but the compliance decision is yours and is worth taking to counsel for anything at scale.
Apify vs Firecrawl: which should I use for an AI agent?
Firecrawl if you mainly need arbitrary web pages turned into clean markdown or JSON for context, since that is exactly its job and the pricing is simpler. Apify if the agent needs structured data from specific platforms such as Google Maps, LinkedIn, Amazon, or Instagram, where a maintained Actor already handles pagination and anti-bot behaviour. Apify's hosted MCP server also exposes thousands of scrapers as agent tools directly, which Firecrawl's narrower surface does not attempt.
Can Apify scrape LinkedIn, Instagram, or Google Maps?
Store carries Actors for all three and they are among the most used on the platform. Quality and reliability vary and these are exactly the targets that change most often, so check an Actor's recent success rate and last update date before depending on it. Note also that scraping logged-in or rate-limited platforms carries account and terms-of-service risk that sits with you, not with Apify.
What happens to my data after a run?
Results land in a Dataset you can preview, export as JSON, CSV, Excel, XML, or RSS, or read through the API. Datasets and key-value stores are deleted automatically after a retention window that depends on your plan, shorter on free than on paid, so anything you need permanently should be exported or pushed to your own storage or a warehouse as part of the workflow.
Who owns Apify?
It is an independent, venture-backed Czech company, founded in 2015 by Jan Curn and Jakub Balada and headquartered in Prague. It has raised a modest amount by category standards, roughly $5 million including a EUR 2.8 million round in 2024, and has reported operating profitably, which is unusual among its better-funded competitors.
Is Crawlee the same thing as Apify?
No. Crawlee is Apify's open-source crawling library for JavaScript and Python, and it runs on your laptop or any cloud with no Apify account involved. Apify is the commercial platform that hosts, schedules, and scales crawlers, supplies proxies and storage, and runs the marketplace. The relationship is deliberate: Crawlee builds credibility and a developer funnel, and the platform is what people pay for when running it themselves stops being convenient.
Editorial verdict
Apify is the most complete web scraping platform a small team can buy without a sales call, and its real asset is the Store: for the sources most go-to-market teams need, someone has already written and is still maintaining the scraper, which is the difference between a two-week engineering project and an afternoon. Underneath it, the proxy pool, browser fleet, storage, and scheduling are the parts people underestimate until they have tried to build them, and Crawlee being open source keeps the lock-in honest. The MCP server has made it one of the more useful data sources to hand an AI agent. The cost of all this is a billing model you have to learn: compute metered by memory times time, credit that expires monthly, and a second layer of fees on paid Actors that no headline price reflects. Budget an hour to measure one representative job before committing, set a spending limit on day one, and check an Actor's success rate before you depend on it. Do those three things and it is very good value; skip them and you will write one of the reviews about unpredictable pricing.
Written by the SaaSTracker editorial team. Awards, when shown, are judged against the published criteria in our methodology.