Apify for web scraping
Apify is a platform of pre-built scrapers, called Actors, and its official server is the second pick for web scraping. It earns that rank as the fallback for sites that fight back: instead of writing a scraper for a tough target, an agent searches the store of 6,000+ Actors, finds one already built for that site, and runs it. Firecrawl leads this task because clean single-page and site extraction is its native job and the more common need.
Apify's angle is reach over a stubborn surface. When a page hides behind JavaScript, pagination, or a login that a general extractor stumbles on, the right move is often a maintained Actor purpose-built for it, and this server is how an agent reaches that library.
How Apify fits
The flow runs through a clear set of tools. search-actors finds an Actor for the task, fetch-actor-details reads its input schema and docs, and call-actor runs it with that input and returns the results; add-actor can register a frequently used Actor as its own callable tool for the session. Long runs are observable: get-actor-run and get-actor-run-list check status, get-actor-log reads execution logs, get-actor-output retrieves the full result, and abort-actor-run stops one that has gone wrong. Results land in datasets, so get-dataset, get-dataset-items (with filtering and pagination), and get-dataset-schema let an agent pull and shape the scraped data.
The limit is that this is an orchestration layer over Actors, not a one-call clean-markdown extractor. Quality and behavior depend on the Actor you pick, and runs are asynchronous, so an agent waits and polls rather than getting an instant response. That is the trade against the siblings. Firecrawl is the cleaner default for turning a page or site into model-ready text, which is why it ranks first. Exa and Tavily are search-first: reach for them to find the right URLs before any scraping. Browserbase is the closer comparison for hard pages, giving you a real headless Chrome to drive directly when no Actor fits. Use Apify when a maintained scraper already exists for your target and you would rather run it than build one.
Tools you would use
| Tool | What it does |
|---|---|
| search-actors | Search the Apify Store to find Actors that match a task. |
| fetch-actor-details | Fetch an Actor's metadata, including its input schema and documentation. |
| call-actor | Run an Actor with the given input and return its results. |
| add-actor | Dynamically register an Actor as a dedicated callable tool for the session. |
| get-actor-run | Retrieve the details and status of a specific Actor run. |
| get-actor-run-list | List Actor runs, optionally filtered by status. |
| get-actor-log | Read the execution log of an Actor run. |
| get-actor-output | Retrieve the complete output produced by an Actor run. |
| abort-actor-run | Stop a running Actor execution. |
| get-dataset | Get metadata about a dataset. |
FAQ
- When should I use Apify instead of Firecrawl for scraping?
- Use Firecrawl for clean extraction of a page or site, which is the common case and why it ranks first. Reach for Apify when a target fights back and a maintained Actor already exists for it: search-actors finds one and call-actor runs it.
- How does an agent find and run a scraper on Apify?
- search-actors locates an Actor for the task, fetch-actor-details reads its input schema, and call-actor runs it. Results land in a dataset that get-dataset-items returns with filtering and pagination.
- Are Apify runs synchronous?
- No. Actor runs are asynchronous, so an agent uses get-actor-run and get-actor-run-list to poll status and get-actor-output to collect results once finished, rather than receiving an instant response.