DEV Community: Nikolas

10 no-API-key Apify Actors for data pipelines (the full portfolio)

Nikolas — Sun, 04 Oct 2026 17:24:06 +0000

All ten run on public sources with no API keys and no logins, and all ten are pay-per-result, so a test costs cents.

Jobs & recruiting

ATS Job Scraper — Greenhouse, Ashby, Lever and SmartRecruiters in one schema, with salary provenance and change hashes.
→ https://apify.com/axiorasolutions/ats-job-scraper

E-commerce

Shopify Variant Scraper — one row per variant: SKU, options, price, compare-at price, discount, stock.
→ https://apify.com/axiorasolutions/shopify-variant-scraper

SEO

SEO Audit Tool — robots/sitemap traversal plus per-URL indexability: canonicals, noindex, hreflang, titles, images, links.
→ https://apify.com/axiorasolutions/sitemap-seo-audit

URL Status Checker — bulk status codes and full redirect chains for broken-link reports and migrations.
→ https://apify.com/axiorasolutions/url-status-checker

News & content

News & RSS Scraper — Google News, RSS 2.0/1.0, Atom and JSON Feed in one schema, with optional full text.
→ https://apify.com/axiorasolutions/news-feed-scraper

Substack Scraper — newsletter archives with engagement: reactions, comments, restacks, word counts.
→ https://apify.com/axiorasolutions/substack-archive-scraper

Mobile

App Store Review Scraper — reviews per country storefront + app profile rows.
→ https://apify.com/axiorasolutions/app-review-scraper

ASO Keyword Scraper — exact App Store rank per keyword per country, with listing metadata.
→ https://apify.com/axiorasolutions/aso-keyword-scraper

Lead-gen & finance

Domain Contact Enricher — emails, phones, socials, tech stack, ATS detection and MX/SPF/DMARC per domain, each value traced to its source page.
→ https://apify.com/axiorasolutions/domain-contact-enricher

SEC EDGAR API — filings, XBRL financial facts and full-text search by ticker or CIK.
→ https://apify.com/axiorasolutions/sec-edgar-api

How they chain

Domain Contact Enricher → detects a company's ATS → feeds the ATS Job Scraper.
SEO Audit Tool → URL list → URL Status Checker for a broken-link report.
News & RSS Scraper + Substack Scraper → the same clean text contract for a RAG index.

Browse all ten: https://apify.com/axiorasolutions

Export a Substack archive with engagement data (posts, reactions, restacks)

Nikolas — Sun, 04 Oct 2026 17:18:55 +0000

The archive API nobody documents

Substack publications expose their archive at /{publication}/api/v1/archive?sort=new&limit=12&offset=0 — the same endpoint the site uses to render its own archive page. It works on *.substack.com and on custom domains like www.noahpinion.blog.

The Substack Scraper pages through it and returns one row per post:

{
  "postId": "218257713",
  "title": "The second Trump presidency is a world-historic failure",
  "subtitle": "How did Trump fumble so badly?",
  "canonicalUrl": "https://www.noahpinion.blog/p/...",
  "publishedAt": "2026-10-03T08:47:17.615Z",
  "audience": "only_paid",
  "isFree": false,
  "isPodcast": false,
  "wordCount": 2933,
  "commentCount": 17,
  "restackCount": 19,
  "reactions": { "❤": 179 },
  "reactionTotal": 179,
  "firstAuthorName": "Noah Smith",
  "publication": "noahpinion.blog"
}

What people use it for

Creator research — which topics drive reactions and restacks across a niche.
Content archiving — a durable, structured copy of your own publication.
Competitive analysis — posting cadence, free/paid mix, average length per publication.

{
  "publications": ["astralcodexten.substack.com", "newsletter.pragmaticengineer.com"],
  "maxPostsPerPublication": 100,
  "audienceFilter": "all"
}

Optional includePostText fetches each free post's page and extracts the body as clean text — paywalled posts return the same truncated preview a non-subscriber sees, which is the honest limit.

Try it

Substack Scraper: Newsletter Posts & Stats — no login needed for public posts.

SEC EDGAR without an API key: filings, XBRL financials, full-text search

Nikolas — Sun, 04 Oct 2026 17:13:45 +0000

EDGAR is free, but it isn't one API

The SEC publishes three useful surfaces, each with its own shape:

Submissions — a company's full filing history (data.sec.gov/submissions/CIK##########.json).
Company facts — XBRL financial values (companyfacts), per concept.
Full-text search — efts.sec.gov across all filings.

The SEC EDGAR API Actor wraps all three behind one input and emits one row schema.

Three modes

{ "queries": ["AAPL"], "mode": "filings", "formTypes": ["10-K"], "maxFilingsPerCompany": 4 }

{ "queries": ["TSLA"], "mode": "facts", "concepts": ["Revenues", "NetIncomeLoss"], "unitsFilter": "USD" }

{ "queries": ["\"generative AI\""], "mode": "search", "searchForms": ["10-K"], "maxSearchHits": 50 }

A filing row

{
  "recordType": "filing",
  "cik": "0001045810",
  "entityName": "NVIDIA CORP",
  "ticker": "NVDA",
  "accessionNumber": "0001045810-26-000021",
  "formType": "10-K",
  "filingDate": "2026-02-25",
  "reportDate": "2026-01-25",
  "primaryDocument": "nvda-20260125.htm",
  "filingUrl": "https://www.sec.gov/Archives/edgar/data/...",
  "isXBRL": true,
  "isInlineXBRL": true
}

Facts rows carry the concept, unit, value, period and the accession that reported it — so a number is always traceable to a filing.

Why use an Actor for this

Polite by default: the Actor sends a declared user agent with contact info, as the SEC requires.
Joins the tedious bits: ticker → CIK lookup, pagination, concept filtering, unit filtering.
Error rows, not failures: an unknown ticker becomes an ok:false row with a hint instead of killing the run.

Try it

SEC EDGAR API: Filings & XBRL Financials — no API key.

Google News + RSS + Atom + JSON Feed: one schema for RAG pipelines

Nikolas — Sun, 04 Oct 2026 17:08:33 +0000

Feeds are the cheapest fresh data on the web

For RAG, monitoring or research, feeds beat scraping: they are small, structured and published for exactly this. The problem is there are at least four formats, plus Google News, and each returns different field names.

The News & RSS Scraper normalises all of them into one row:

{
  "articleUid": "07aff4e08a2282d9",
  "feedTitle": "BBC News",
  "sourceType": "rss-2.0",
  "title": "OpenAI fires workers for mishandling sensitive information",
  "titleWithoutPublisher": "OpenAI fires workers for mishandling sensitive information",
  "url": "https://www.bbc.co.uk/news/articles/...",
  "publisherDomain": "bbc.co.uk",
  "publishedAt": "2026-10-02T08:20:32.000Z",
  "ageHours": 29,
  "summary": "...",
  "categories": [],
  "imageUrl": null,
  "contentHash": "d6dbba40b2d3507d"
}

Mix Google News and plain feeds

{
  "sources": [
    "gnews:artificial intelligence",
    "gnews-topic:TECHNOLOGY",
    "https://techcrunch.com/feed/",
    "https://daringfireball.net/feeds/json",
    "theverge.com"
  ],
  "maxItemsPerSource": 100
}

gnews: runs a Google News search (quotes and when:7d work).
gnews-topic: pulls a Google News topic.
a plain feed URL is read directly; a website URL is auto-discovered to its feed.
Feed types are detected automatically: RSS 2.0, RSS 1.0/RDF, Atom 1.0, JSON Feed.

Built for pipelines

Dedup strategies: by URL, normalised title, feed GUID, or none.
Date filters relative (24 hours, 7 days) or absolute.
Optional full text — fetches each article and extracts the body as clean plain text, with the page's own contentHash.
Canonical URLs, so Google News redirects don't poison your index.

Try it

News & RSS Scraper: Google News to JSON — no API key, no login.

A sitemap SEO audit that actually checks indexability (not just URLs)

Nikolas — Sun, 04 Oct 2026 17:03:22 +0000

Extracting URLs is the easy part

A sitemap gives you a list. What you actually need to know is whether those pages can rank: do they return 200, do they self-canonical, are they accidentally noindexed, do they have a title of a sane length, is the hreflang cluster reciprocal?

The SEO Audit Tool does the full pass, bounded:

Fetches robots.txt and follows every declared Sitemap:.
Walks nested sitemap index files up to your cap.
Fetches each URL (robots-aware by default) and reports.

What each audited URL carries

{
  "recordType": "page",
  "url": "https://example.com/pricing",
  "httpStatus": 200,
  "finalUrl": "https://example.com/pricing",
  "redirectCount": 0,
  "contentType": "text/html",
  "title": "Pricing — Example",
  "metaDescription": "...",
  "h1Count": 1,
  "canonicalUrl": "https://example.com/pricing",
  "isNoindex": false,
  "isIndexable": true,
  "hreflang": [{ "lang": "en", "url": "..." }],
  "imagesMissingAlt": 3,
  "internalLinks": 42,
  "findings": [
    { "id": "title-too-short", "severity": "low", "message": "Title is 14 characters.", "evidence": "Pricing — Example" }
  ]
}

Findings are severity-ranked, so the dataset sorts into a to-do list.

Two modes

extract-urls — cheap, returns the URL inventory with lastmod/changefreq/priority. Use it to size a site before paying for a full audit.
audit — fetches and analyses every URL.

{
  "sites": ["example.com"],
  "mode": "audit",
  "maxUrlsPerSite": 500,
  "maxSitemapsPerSite": 30
}

The honest limit

If a site has no sitemap, there is nothing to audit. The Actor tells you so (EMPTY_RESULT) instead of silently crawling the whole domain, because that would blow your budget without warning.

Try it

SEO Audit Tool: Sitemap & Indexability — point it at a domain or a direct sitemap URL.

Scrape any Shopify store's variants (price, SKU, stock) without an API key

Nikolas — Sun, 04 Oct 2026 16:58:12 +0000

The public feed most people forget

Every Shopify store exposes its catalogue at /{store}/products.json — the same feed the storefront's own JavaScript uses. No API key, no app install, no OAuth. You just need to treat it like the fragile public endpoint it is.

One row per variant, not per product

Price, SKU and stock live on the variant, so a shirt in five sizes is five rows. The Shopify Variant Scraper returns:

{
  "store": "allbirds.com",
  "productTitle": "Wool Runner Go",
  "variantTitle": "US 10 / Natural Black",
  "sku": "WRG-NB-10",
  "price": 140,
  "compareAtPrice": 160,
  "discountPercent": 12.5,
  "isOnSale": true,
  "available": true,
  "option1": "US 10",
  "option2": "Natural Black",
  "vendor": "Allbirds",
  "productType": "Shoes",
  "tags": ["sale"],
  "images": ["https://cdn.shopify.com/..."],
  "variantUid": "allbirds.com:123456:789012",
  "productHash": "b41c9d2e77f0a183"
}

productHash is a change-detection key: diff two scheduled runs to see exactly which variants changed price or stock.

Filters that cut the bill

The input lets you narrow before rows are written, so filters reduce both the dataset and the number of billed variants:

{
  "stores": ["allbirds.com", "kith.com"],
  "collections": ["sale"],
  "onSaleOnly": true,
  "maxProductsPerStore": 100,
  "maxVariantsTotal": 2000
}

Handle the failure modes

The public feed is not always friendly, and the Actor reports each case as an error row instead of failing the run:

404 → the store is not Shopify (or the feed is disabled) → UNSUPPORTED_SOURCE.
429 → the store rate-limited you → RATE_LIMITED.
Empty → feed exists but the catalogue is private → EMPTY_RESULT.

That means a mixed list of 500 domains gives you data for the real Shopify stores and a clear reason for every miss.

Try it

Shopify Variant Scraper: Price, SKU & Stock — no API key, one row per variant.

A hiring-signal pipeline in 15 minutes: domains ATS job postings

Nikolas — Sat, 03 Oct 2026 15:53:09 +0000

The goal

You have a list of company domains — prospects, competitors, a market map. You want a feed of their open roles, refreshed weekly, with a diff of what changed. No vendors, no servers, no keys.

Two Actors do it.

Step 1 — domain in, hiring board out

The Domain Contact Enricher reads a company's site and detects which ATS it uses. It emits a ready-to-use input:

{
  "domain": "example.com",
  "atsProvider": "greenhouse",
  "atsJobScraperInput": "greenhouse:example",
  "technologyIds": ["nextjs", "cloudflare"],
  "emailInfrastructure": { "mailProvider": "Google Workspace", "hasSpf": true, "hasDmarc": true }
}

Run it over your whole list:

{ "domains": ["stripe.com", "shopify.com", "tesla.com"], "maxPagesPerDomain": 3 }

Collect the atsJobScraperInput values that are not null.

Step 2 — boards in, job rows out

Feed those strings into the ATS Job Scraper:

{
  "boards": ["greenhouse:stripe", "ashby:linear"],
  "maxJobsPerBoard": 200,
  "postedAfter": "14 days"
}

You get one normalised row per job with salary.evidence, workplaceType, postedAt and two change-detection keys:

jobUid — stable identity → spot new and removed roles,
recordHash — content hash → spot edited postings.

Step 3 — schedule and diff

Add an Apify Schedule (weekly), then diff consecutive runs:

postedAfter: "14 days" keeps each run small and current.
New jobUid = new role = a sales or talent signal.
Changed recordHash on an old role = the description or salary moved.

If you want emails alongside the jobs, the Domain Enricher already returned contacts with their source page, so the same run gives you "who to talk to" and "what they are hiring for".

Why this beats a scraping stack

No API keys and no logins anywhere in the chain.
The actors report per-domain and per-board failures as error rows, so one dead board never fails the run.
Both are pay-per-result: a 50-domain, 500-job refresh costs cents.

Start with the Domain Contact Enricher, then chain the ATS Job Scraper.

Greenhouse vs Ashby vs Lever vs SmartRecruiters: which job API should you scrape?

Nikolas — Sat, 03 Oct 2026 15:47:53 +0000

If you scrape job boards, these four cover a huge share of tech employers. They are also four different APIs with four different conventions. Here is the honest comparison I wish I had before writing my fourth parser.

Greenhouse

Endpoint: boards-api.greenhouse.io/v1/boards/{token}/jobs

One request returns every job. Add ?content=true for descriptions.
Trap: content=true roughly 12×'s the payload (5.4 MB vs 436 KB for a 715-job board). If you only need N jobs, fetch the list first and then per-job /jobs/{id} (8 KB each).
content is double-encoded HTML — entities then tags.
Salary is sometimes in metadata, a label/value array ("Salary Range" → "$180k–$230k"), and often nowhere.

Ashby

Endpoint: api.ashbyhq.com/posting-api/job-board/{token}?includeCompensation=true

The only one of the four with structured compensation: numbers live on compensation.summaryComponents[] where compensationType === "Salary", not on the tier object most code reads first.
Trap: isRemote: true is set for Hybrid roles. Trust the workplaceType string ("Remote" / "Hybrid" / "OnSite"), or your "remote only" filter silently returns hybrid jobs.
Board tokens are case-sensitive, and no server-side limit exists — a board like OpenAI is ~14 MB.

Lever

Endpoint: api.lever.co/v0/postings/{token}?mode=json

Supports &limit=N, which is genuinely useful for large boards (19 KB for 2 postings vs 775 KB for all).
Trap: the public endpoint has no salaryRange field at all. Any tool that reports ats-field salary evidence for Lever is inventing it.
Locations hide in categories.allLocations; workplace type is a hyphenated string.

SmartRecruiters

Endpoint: api.smartrecruiters.com/v1/companies/{token}/postings?limit=100&offset=N

Clean pagination with limit/offset and a totalFound count.
Trap: the public API is off by default. Of twenty well-known companies I tested, only a handful returned anything. Document that or users will read empty boards as your bug.
Descriptions require a second request per posting (/postings/{id}) and live inside jobAd.sections.

The summary table

	Greenhouse	Ashby	Lever	SmartRecruiters
Pagination / limit	no	no	`limit`	`limit`+`offset`
Structured salary	sometimes (metadata)	yes	no	no
Description in list	with `content=true`	yes	yes	per-posting
Workplace type	no	`workplaceType`	string	`remote` + `hybrid`
Company name in payload	via board metadata	no	no	from first posting

What to build instead of four parsers

I put the four behind one schema — one row per job with title, locations, workplace type, salary with evidence provenance, apply URL, and stable jobUid/recordHash for change detection. It is an Apify Actor, so there is nothing to host:

→ ATS Job Scraper: Greenhouse, Ashby & Lever

{ "boards": ["greenhouse:airtable", "ashby:Linear", "lever:spotify"], "maxJobsPerBoard": 100 }

No API key, and a 5-job test costs a fraction of a cent.

ASO keyword tracking: get the exact App Store rank per country (with code)

Nikolas — Sat, 03 Oct 2026 15:39:30 +0000

Exact rank, not a computed score

Most "ASO tools" show you a made-up difficulty number. What you actually want is the boring truth: for the keyword habit tracker in the US storefront, which apps are at positions 1–50 today, and what does each listing look like?

The ASO Keyword Scraper returns exactly that — one row per app per keyword per storefront, using Apple's own relevance order:

{
  "recordType": "ranking",
  "keyword": "habit tracker",
  "storefront": "us",
  "rank": 1,
  "appName": "Habit Tracker - Daily Goals",
  "developerName": "Example Labs",
  "averageUserRating": 4.82,
  "userRatingCount": 128411,
  "primaryGenre": "Health & Fitness",
  "formattedPrice": "Free",
  "keywordMatchInTitle": true,
  "currentVersionReleaseDate": "2026-09-24T10:00:00Z",
  "appStoreUrl": "https://apps.apple.com/us/app/..."
}

Signals that matter more than a difficulty score

userRatingCount — a rank-3 app with 400 ratings is a weak incumbent. A rank-3 app with 900k ratings is a wall.
keywordMatchInTitle — the strongest ranking input Apple exposes. If none of the top 10 use your keyword, that is an opening.
currentVersionReleaseDate — an app not updated in two years is decaying.

Track rivals across storefronts

The same app can rank 3rd in the US and 40th in Germany. Add both countries and compare:

{
  "keywords": ["habit tracker", "budget app"],
  "countries": ["us", "de"],
  "resultsPerKeyword": 50
}

You can also pass apps to resolve listing metadata directly (rank stays null), which is handy for a competitor dashboard.

Run it from code

curl -X POST "https://api.apify.com/v2/acts/axiorasolutions~aso-keyword-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords":["habit tracker"],"countries":["us","de"],"resultsPerKeyword":25}'

Schedule it weekly and diff on recordHash to catch rank moves.

Try it

ASO Keyword Scraper — no API key, and it handles the storefront/language details for you.

5 no-API-key data Actors for recruiting, ASO, lead-gen and SEO

Nikolas — Sat, 03 Oct 2026 15:33:40 +0000

A lot of "data APIs" want a credit card, a sales call and a rate limit before you see a single row. These five run on public sources with no API key, so you can test them in minutes and schedule them when they earn their place.

1. ATS Job Scraper — Greenhouse, Ashby, Lever, SmartRecruiters

One row per open role, four providers, one schema. Salary carries an evidence field so you know whether a number came from the ATS itself, the description text, or nowhere. recordHash gives you change detection for free.

→ apify.com/axiorasolutions/ats-job-scraper

2. App Store Review Scraper — reviews per country

Apple stores reviews per storefront, so this targets the countries you care about. Rating, body, version and helpful votes per review, plus an app profile row.

→ apify.com/axiorasolutions/app-review-scraper

3. ASO Keyword Scraper — exact rank per keyword and country

The honest version of ASO data: Apple's exact order, with rating counts and "keyword in title" flags so you can tell a weak incumbent from a wall.

→ apify.com/axiorasolutions/aso-keyword-scraper

4. Domain Contact Enricher — domains into contactable records

Emails, phones, socials, tech stack, ATS detection and MX/SPF/DMARC — one row per domain, every value traced to its source page.

→ apify.com/axiorasolutions/domain-contact-enricher

5. URL Status Checker — bulk status and redirect chains

Feed it a URL list (or the output of a sitemap crawl) and get status codes, full redirect chains, timing and page facts. The broken-link report you run before every migration.

→ apify.com/axiorasolutions/url-status-checker

Why they chain together

The Domain Enricher detects the ATS a company uses and emits an input string for the Jobs Actor. The Sitemap Audit emits URLs for the Status Checker. Each is useful alone and better as a pipeline.

All five are pay-per-result, so a small test costs cents and a full run is predictable. No keys, no logins, no browser.

Bulk URL and redirect-chain audits: a 2-minute safety net before a migration

Nikolas — Sat, 03 Oct 2026 15:28:29 +0000

The five minutes before you ship a migration

You changed your URL structure, added a trailing slash policy, or moved a domain. The only thing standing between you and a traffic cliff is a redirect map that actually works. Testing 500 URLs by hand is not a plan.

The URL Status Checker takes a list of URLs and returns, per row:

HTTP status and status category,
the full redirect chain, hop by hop,
the final URL and whether the redirect crossed domains,
response time and content type,
and for HTML responses: title, h1, canonical, meta robots.

{
  "requestedUrl": "http://example.com/old-page",
  "httpStatus": 200,
  "isRedirect": false,
  "redirectCount": 2,
  "redirectChain": [
    { "status": 301, "to": "https://example.com/old-page" },
    { "status": 301, "to": "https://example.com/new-page" }
  ],
  "isCrossDomainRedirect": false,
  "finalUrl": "https://example.com/new-page",
  "responseMs": 143,
  "title": "New page",
  "metaRobots": "index,follow"
}

Recipes

Broken-link report — set filterByStatus: ["404","410","500"] and you get only the pages that are actually dead, and you are only billed for those.

Redirect QA — feed the old URL list in, sort by redirectCount and look for chains longer than one hop or unexpected cross-domain hops. Both hurt SEO.

Crawl audit handoff — the Sitemap SEO Audit dataset's URL column pastes straight into this Actor.

Input

{
  "urls": ["https://example.com", "http://example.com/old-page"],
  "method": "GET",
  "followRedirects": true
}

A non-2xx response is a result, not a failed run — you get a row for every URL you asked about.

Try it

URL Status Checker — no API key, and HEAD mode roughly halves the time for very large sweeps.

Company enrichment without a data vendor: domains to emails, tech stack and MX

Nikolas — Sat, 03 Oct 2026 15:23:18 +0000

What a lead list actually needs

You have a list of company domains. You want, per company:

contact emails and phone numbers,
social profiles,
the technology stack they run,
the ATS they use for hiring,
and their email infrastructure (MX provider, SPF, DMARC).

The hard requirement is not volume. It is provenance — knowing which page each value came from, so you can defend a contact when someone asks "where did you get this?"

Every value carries its source

The Domain Contact Enricher returns one row per domain. Contacts are ranked by confidence, and each carries the URL where it was found:

{
  "domain": "example.com",
  "companyName": "Example Inc.",
  "emailCount": 2,
  "emails": [
    { "email": "hello@example.com", "confidence": "high", "isRoleAccount": true, "sourceUrl": "https://example.com/contact" }
  ],
  "socialProfiles": { "linkedin": "https://www.linkedin.com/company/example", "github": "https://github.com/example" },
  "technologyIds": ["nextjs", "cloudflare", "hubspot"],
  "atsProvider": "greenhouse",
  "atsJobScraperInput": "greenhouse:example",
  "emailInfrastructure": {
    "mailProvider": "Google Workspace",
    "hasSpf": true,
    "hasDmarc": true
  }
}

The atsJobScraperInput field chains directly into the ATS Job Scraper — domain in, hiring board out.

An honest coverage note

Modern companies increasingly hide behind contact forms. This actor returns contacts when the site publishes them on its home, contact, about, team or imprint pages — it does not invent addresses or scrape private data. If it finds none, you get a profile row with the technology and email infrastructure, not a fabricated email. That is the correct behaviour for a list you intend to email.

Usage

{
  "domains": ["stripe.com", "shopify.com", "tesla.com"],
  "maxPagesPerDomain": 4,
  "includeTechnologies": true,
  "includeDnsSignals": true
}

It also respects robots.txt by default and reports unreachable domains as unbilled error rows.

Try it

Domain Contact Enricher — bulk mode, no API key, every value traceable.