Quora Scraper

Quora Scraper — Questions, Answers, Profiles & Exact Timestamps

Quora Scraper extracts questions, answers, user profiles, topics and Spaces from Quora by keyword search or direct URL — no Quora account or login required. It returns five distinct content types in one run, and every answer carries both Quora's relative post age ("3y") and an absolute ISO-8601 timestamp, so you can sort and diff results without re-parsing fuzzy dates. Every response is structured JSON, ready to pass straight into an LLM prompt, a vector store, or a monitoring pipeline. Point it at a topic, a competitor's brand name, or a list of question URLs, and it comes back with clean, typed rows for whatever Quora actually shows a logged-out visitor.

What is Quora Scraper?

Quora Scraper is a query-driven Apify Actor that turns Quora keyword searches and direct Quora URLs into structured dataset rows. It queries Quora through two paths — a keyword search that resolves each term to relevant Quora URLs, and a direct-URL list you paste in yourself — and classifies every URL into one of four page types (question, profile, topic, Space) before scraping it. No Quora account, login, or cookies are required — the Actor reads only what a signed-out visitor can see, confirmed by the src/main.py fetch path, which never sends authentication headers or session cookies.

What sets it apart from a plain page-text scraper is the dual timestamp on every answer: alongside Quora's own relative string ("3y", "2mo"), it computes and attaches an absolute answer_created_at ISO-8601 date from the same underlying epoch — a field pair none of the three highest-ranked competing Quora scrapers on the Apify Store expose together (checked 2026-07-25; see the comparison in the FAQ below).

As a Quora data extractor it is built to be a practical stand-in for the API alternative Quora doesn't offer — the same Q&A dataset, engagement metrics, and profile data a manual export would take days to assemble by hand, delivered as one Apify dataset per run.

Key capabilities:

• 🔍 Keyword search — resolves each search term to relevant Quora URLs automatically, no need to construct search URLs by hand
• 🔗 Bulk direct URLs — paste any mix of question, profile, topic, or Space URLs and scrape them in one run
• 💬 Full answer pagination — collects answers past the first page via Quora's own GraphQL pagination, up to the maxResults ceiling per question
• 🤖 AI-answer flagging — every answer row carries is_ai_answer, set from Quora's own isMachineAnswer field
• 🛡️ Self-escalating proxy — starts with no proxy at all and only pays for datacenter, then residential, proxy when Quora actually blocks a request
• 🧭 Headless-browser last resort — a page that stays blocked over plain HTTP is re-rendered in a real Chromium browser before the Actor gives up on it

What data can you get with Quora Scraper?

Quora Scraper returns five content types in a single run, distinguished by the content_type field on every row.

Result Type	Extracted Fields	Primary Use Case
Question	title, url, answer_count, follow_count, topics, source_query, source_url	Content ideation, trend and demand research
Answer	answer_text, answer_url, author_name, author_url, author_credentials, upvotes, comments_count, shares_count, answer_timestamp, answer_created_at, is_ai_answer, question_title, question_url	Sentiment analysis, competitive intelligence, LLM training data
Profile	name, url, bio, credentials, profile_image_url, follower_count, following_count, answer_count, question_count, total_views	Expert discovery, lead generation, influencer mapping
Topic	name, url, description, follower_count, question_count	Niche sizing, category research
Space	name, url, description, follower_count, post_count, contributor_count	Community mapping, niche group discovery

Every row also carries content_type, source_url (the URL the row came from) and scrape_timestamp (when the Actor fetched it); question and answer rows resolved via keyword search additionally carry source_query, the exact keyword that led to them, left as an empty string for rows found through directUrls. A question row's topics array lists the topic names Quora itself tags the question with — pass one of those names through directUrls as quora.com/topic/<name> in a follow-up run to pull that Topic's own follower and question counts, and cross-reference the two.

Content types are not evenly distributed per input: a question URL yields one question row plus up to maxResults answer rows, while a profile, topic, or Space URL always yields exactly one row of its own type. A keyword in searchQueries can resolve to a mix of all four URL types, since the search step isn't restricted to questions alone.

Exact answer timestamps

Quora only ever shows a visitor a relative age like "3y" or "5mo" on an answer — never a calendar date. Quora Scraper reads the same microsecond epoch Quora's frontend uses to compute that string and returns both values on every answer row:

{
  "answer_timestamp": "3y",
  "answer_created_at": "2022-06-14T07:46:04+00:00"
}

answer_timestamp (source: relative_time() in src/main.py) reproduces exactly what a Quora visitor would see. answer_created_at (source: iso_from_micros()) is the same moment as an unambiguous, sortable ISO-8601 UTC string — so you can rank answers by true recency, bucket them by month or quarter, or feed a fixed cutoff date into a filter, none of which is possible from the relative string alone. If the underlying creationTime field is missing from Quora's payload, answer_created_at is null rather than an empty string.

User profiles

Profile rows carry more than a name and URL: credentials (Quora's "Studied at…" / "Works at…" line, rendered from the same rich-text structure Quora uses for answer bylines), total_views (Quora's all-time public-content view counter), and both follower_count and following_count. Combined with answer_count and question_count, this is enough to rank a list of Quora contributors by influence and topical activity without opening a single profile page by hand — useful for building a shortlist of subject-matter voices to pitch, interview, or track.

⚠️ Why not build this yourself?

Quora's official /graphql endpoint returns a Cloudflare "Just a moment" challenge on general-purpose cloud infrastructure — including Apify's — even through a residential proxy, which is why the answer-pagination GraphQL call in this Actor is a fallback, not the primary path (see src/main.py, _fetch_batch). The primary answer source is Quora's own server-rendered HTML: every page embeds its data as a sequence of obfuscated .push() JSON blobs that have to be located with regex, unescaped twice, and pattern-matched against a set of "does this look like a real answer object" heuristics (answers_from_blobs, _looks_like_answer) to tell real content apart from an empty challenge-page stub.

Quora also has no public search or content API for third-party developers, so there is no documented endpoint to build against in the first place — a keyword-to-URL resolution step has to go through a general search engine instead (see the "How to scrape Quora" section below). That search step brings its own moving parts: a session token (vqd) has to be pulled out of an initial HTML response and reused across every paginated results request, and a result page can itself come back as an anomaly-detection block that has to be recognized and stopped on, rather than mistaken for "no more results." Maintaining that whole page-parsing layer — the blob regexes, the formkey and hash extraction for GraphQL pagination, the search token handling, and the proxy ladder that keeps a session's cookies valid across an escalation — is the ongoing engineering cost this Actor absorbs so you don't have to rebuild it every time Quora or the search engine it depends on changes their frontend.

How to scrape Quora with Quora Scraper?

1. Open Quora Scraper on the Apify Store and click Try for free (or go straight to the Input tab if you already have it in your account).
2. Enter one or more terms in searchQueries, paste URLs into directUrls, or both — at least one of the two is required, or the run exits immediately with nothing to do.
3. Set maxResults to the number of results you want per keyword (and per question's answers) — default 50, up to 50,000.
4. Click Start and watch the run log — every proxy escalation and every question/profile/topic/Space scraped is logged live.
5. Open the Output tab, switch between the Overview / Questions / Answers / Profiles / Topics / Spaces dataset views, and export as JSON, CSV, Excel, XML, or RSS.

Example request body:

{
  "searchQueries": ["python programming"],
  "directUrls": ["https://www.quora.com/What-is-Python-primarily-used-for"],
  "maxResults": 25
}

Quora Scraper is billed under Apify's Pay-Per-Event pricing model: every row actually written to the dataset — question, answer, profile, topic, or Space — is charged once under the row_result event. A URL that fails to scrape (blocked, removed, or not a recognized Quora page type) is logged and skipped rather than pushed, so it is never billed. Check the Pricing tab on the Actor's Store listing for the current per-event rate.

How to run multiple queries in one job

Both searchQueries and directUrls are arrays — add as many keywords or URLs as you need and they all run in the same job. Every URL, whether resolved from a keyword or pasted directly, is scraped through the same bounded-concurrency pool: the concurrency input caps how many Quora pages are fetched in parallel (default 6, 1–20), so a batch of 50 URLs at concurrency: 10 processes roughly ten at a time rather than sequentially.

⬇️ Input

Quora Scraper takes two ways to tell it what to scrape — a list of search keywords, a list of direct URLs, or both — plus five tuning parameters. Nothing is required; the Actor simply exits with a warning if both searchQueries and directUrls are empty.

Parameter	Required	Type	Default	Constraints	Description
searchQueries	No	array of strings	[]	—	Keywords to search on Quora. Each keyword is resolved to relevant Quora URLs and scraped automatically. Leave empty to only use direct URLs.
directUrls	No	array of strings	[]	—	Quora URLs to scrape in bulk — questions, profiles (/profile/...), topics (/topic/...) or Spaces (/q/...).
maxResults	No	integer	50	min 1, max 50000	Max results per search keyword, and max answers scraped per question URL — the same limit governs both.
concurrency	No	integer	6	min 1, max 20	How many Quora pages to fetch in parallel. Higher is faster but more likely to trip Quora's rate limits.
requestDelay	No	integer (seconds)	0.5*	min 0, max 30	Polite delay added before each request. Leave blank for the default of ~0.5s — a small random jitter is always added on top of whatever value you set.
useBrowserFallback	No	boolean	true	—	When a page is hard-blocked over plain HTTP, re-render it in a headless Chromium browser as a last resort. Turn off for faster, cheaper runs that never launch a browser.
proxyConfiguration	No	object (proxy editor)	{"useApifyProxy": true}	—	Apify Proxy configuration. The scraper always starts with a direct request (no proxy) and only escalates to datacenter, then residential, if Quora blocks it — then sticks with residential for the rest of the run.

* requestDelay has no default set in the input schema itself (only minimum/maximum); leaving the field blank falls back to 0.5 seconds in the Actor's own code.

Full example input:

{
  "searchQueries": ["machine learning", "startup funding advice"],
  "directUrls": [
    "https://www.quora.com/What-is-Python-primarily-used-for",
    "https://www.quora.com/profile/Rahat-Ahmed-475",
    "https://www.quora.com/topic/Artificial-Intelligence",
    "https://www.quora.com/q/data-science-central"
  ],
  "maxResults": 25,
  "concurrency": 6,
  "useBrowserFallback": true,
  "proxyConfiguration": { "useApifyProxy": true }
}

Common pitfall: only paste question, profile (/profile/...), topic (/topic/...) or Space (/q/...) URLs into directUrls. A Quora search-results URL (quora.com/search?q=...) doesn't match any of those path prefixes, so the Actor classifies it as a question page by default, finds no question data on it, logs a skip warning, and pushes zero rows for it. Use searchQueries for keyword search instead of pasting a search URL.

Second pitfall: setting proxyConfiguration.useApifyProxy to false doesn't just skip the starting proxy tier — it disables the entire escalation ladder for the run. Every request stays direct even if Quora blocks it, and the only remaining rescue for a blocked page is the headless-browser fallback (if useBrowserFallback is still on). Leave useApifyProxy at its default true unless you have a specific reason to force direct-only requests.

⬆️ Output

Every scraped item is pushed to the Actor's default dataset as a flat JSON object, immediately as it's found — nothing is buffered until the end of the run. Export the dataset as JSON, CSV, Excel, XML, RSS, or query it directly through the Apify API. The Console's dataset view offers six pre-built tables — Overview, Questions, Answers, Profiles, Topics, and Spaces — but those views only render a subset of columns for readability; the underlying rows carry every field listed in the data-coverage table above.

Scraped results

[
  {
    "content_type": "question",
    "title": "What is Python primarily used for?",
    "url": "https://www.quora.com/What-is-Python-primarily-used-for",
    "answer_count": 214,
    "follow_count": 3821,
    "topics": ["Python (programming language)", "Programming Languages", "Computer Programming"],
    "source_url": "https://www.quora.com/What-is-Python-primarily-used-for",
    "source_query": "python programming",
    "scrape_timestamp": "2026-07-25T09:12:03.118422+00:00"
  },
  {
    "content_type": "answer",
    "title": "What is Python primarily used for?",
    "url": "https://www.quora.com/What-is-Python-primarily-used-for/answer/Rahat-Ahmed-475",
    "answer_text": "Python is a high-level, general-purpose programming language widely used for web development, data science, automation and machine learning...",
    "answer_url": "https://www.quora.com/What-is-Python-primarily-used-for/answer/Rahat-Ahmed-475",
    "author_name": "Rahat Ahmed",
    "author_url": "https://www.quora.com/profile/Rahat-Ahmed-475",
    "author_credentials": "Software Engineer",
    "upvotes": 214,
    "comments_count": 6,
    "shares_count": 12,
    "answer_timestamp": "3y",
    "answer_created_at": "2022-06-14T07:46:04+00:00",
    "is_ai_answer": false,
    "question_title": "What is Python primarily used for?",
    "question_url": "https://www.quora.com/What-is-Python-primarily-used-for",
    "source_url": "https://www.quora.com/What-is-Python-primarily-used-for",
    "source_query": "python programming",
    "scrape_timestamp": "2026-07-25T09:12:05.554871+00:00"
  },
  {
    "content_type": "profile",
    "title": "Rahat Ahmed",
    "name": "Rahat Ahmed",
    "url": "https://www.quora.com/profile/Rahat-Ahmed-475",
    "bio": "Building developer tools. Writing about Python, systems design and startups.",
    "credentials": "Software Engineer",
    "profile_image_url": "https://qph.cf2.quoracdn.net/main-thumb-example.jpg",
    "follower_count": 5920,
    "following_count": 340,
    "answer_count": 812,
    "question_count": 14,
    "total_views": 4210233,
    "source_url": "https://www.quora.com/profile/Rahat-Ahmed-475",
    "scrape_timestamp": "2026-07-25T09:12:07.902118+00:00"
  },
  {
    "content_type": "topic",
    "title": "Artificial Intelligence",
    "name": "Artificial Intelligence",
    "url": "https://www.quora.com/topic/Artificial-Intelligence",
    "description": "Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals and humans.",
    "follower_count": 187234,
    "question_count": 42011,
    "source_url": "https://www.quora.com/topic/Artificial-Intelligence",
    "scrape_timestamp": "2026-07-25T09:12:09.331904+00:00"
  },
  {
    "content_type": "space",
    "title": "Data Science Central",
    "name": "Data Science Central",
    "url": "https://www.quora.com/q/data-science-central",
    "description": "A community for data scientists to share knowledge, ask questions, and discuss trends in analytics and machine learning.",
    "follower_count": 8912,
    "post_count": 634,
    "contributor_count": 47,
    "source_url": "https://www.quora.com/q/data-science-central",
    "scrape_timestamp": "2026-07-25T09:12:11.007532+00:00"
  }
]

Field presence depends on content_type — a question row never carries answer_text, and an answer row never carries follower_count. Any field Quora didn't return for a given item comes back as null (or an empty string for text fields such as bio or description) rather than being omitted from the object, so every row of the same content_type has an identical key set.

How can I use the data extracted with Quora Scraper?

• 📈 Content marketers and SEOs — pull title and topics from question rows in your niche to find real, phrased-as-asked content angles and FAQ copy, then cross-reference answer_count and upvotes to see which of those questions already have thin or weak answers worth outranking.
• 🤖 AI engineers and LLM developers — an agent issues a query, this Actor returns structured JSON, and the agent passes answer_text plus author_credentials into the model as grounded context — turning a static LLM into one that can cite what real people said on a topic, with a real source URL attached.
• 📊 Market researchers — track upvotes, comments_count and is_ai_answer across a keyword set to gauge sentiment and how much of a topic's discussion is human-authored versus AI-generated on Quora right now.
• 🧑‍💼 Lead generation and recruiting teams — filter profile rows by credentials, follower_count and answer_count to shortlist active, credentialed contributors in a niche before reaching out.
• 🔬 Researchers and dataset builders — the is_ai_answer flag on every answer row lets you split a collected corpus into human-written and AI-generated text before it goes anywhere near an NLP pipeline or a benchmark set, without hand-labeling a single row.

How do you monitor Quora activity over time?

Monitoring Quora discussions means running the same keyword set or URL list on a schedule and diffing the results, since Quora itself gives you no changelog or webhook for a question's activity. What changes between two runs of the same question or profile URL is what tells you something moved: answer_count and follow_count climbing on a question row means the topic is heating up; upvotes and comments_count climbing on a specific answer row means that answer is gaining traction; follower_count and total_views climbing on a profile row means that contributor's reach is growing.

A simple workflow: run Quora Scraper on a fixed list of question and profile URLs (or a keyword set) on a daily or weekly Apify Schedule, keep each run's dataset, and diff the current run against the previous one on answer_count, upvotes, comments_count and follower_count. Alert when a question crosses a follower or answer-count threshold you care about, or when a specific answer's upvotes jumps sharply — that's usually the signal that it started ranking or got shared elsewhere. Because answer_created_at is an absolute timestamp rather than a relative string, you can also filter each run to "answers posted since my last run" without re-parsing "2mo" into a date every time.

The Actor itself has no built-in cron or webhook — schedule repeated runs with Apify Schedules in the Console (or the Schedules API), and use Apify Webhooks (or an integration like Zapier or Make, both available from the Actor's Integrations tab) to push a notification or dataset export whenever a scheduled run finishes.

Integrate Quora Scraper and automate your workflow

Quora Scraper works with any language or tool that can send an HTTP request, through the Apify API and the official apify-client SDKs.

REST API with Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("<YOUR_USERNAME>/quora-scraper").call(run_input={
    "searchQueries": ["startup funding advice"],
    "maxResults": 25,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item["content_type"] == "answer":
        print(item["author_name"], "-", item["upvotes"], "upvotes -", item["answer_timestamp"])

Any other HTTP client works the same way — call the Actor's run endpoint with your Apify API token, poll or wait for the run to finish, then fetch its dataset:

curl -X POST "https://api.apify.com/v2/acts/<YOUR_USERNAME>~quora-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"directUrls": ["https://www.quora.com/What-is-Python-primarily-used-for"], "maxResults": 25}'

Scheduled monitoring and delivery

Set up a recurring run from the Actor's Schedule tab in the Apify Console (any cron expression), or create one via the Schedules API. Pair it with an Apify Webhook on the ACTOR.RUN.SUCCEEDED event to push each run's dataset to an external endpoint, or use the built-in Zapier/Make/Google Sheets integrations from the Actor's Integrations tab — no polling loop required on your side.

Is it legal to scrape Quora results?

Scraping publicly accessible Quora pages — the same pages any signed-out visitor can load without a login — is generally lawful; Quora Scraper only reads what's already served to an anonymous browser, confirmed by the fact that no cookie or authentication header is sent in its request path. Because profile rows carry personal data (names, bios, follower counts tied to an identifiable person), GDPR and CCPA considerations apply if you collect, store, or process EU or California residents' profile data — you are the data controller for what you do with it. Question, answer, topic and Space content is closer to business/public-record data, where Quora's own Terms of Service and database-rights law are the more relevant framing. Scraping for AI training and scraping for operational monitoring carry different risk profiles and should be evaluated separately. Consult your legal team for commercial use cases involving bulk data storage or resale.

❓ Frequently asked questions

Does Quora Scraper support other languages or regions?

No — there is no language or region input parameter. Quora Scraper reads whatever language a given Quora page is actually published in; keyword search resolution runs against a fixed search region internally (us-en) regardless of the keyword's own language, so non-English keyword search results may be less complete than pasting direct non-English Quora URLs into directUrls.

Can I control which answers are returned, or their order?

Not directly. There is no sortAnswersBy or minimum-upvotes filter — answers come back in the order Quora itself serves them: first the answers Quora server-renders into the question page, then, for questions with more answers than that first page, additional pages via Quora's own GraphQL pagination, up to your maxResults limit. Filter or re-sort by upvotes, comments_count or answer_created_at after the run if you need a specific order.

How does Quora Scraper handle Quora's anti-bot measures?

By starting with the lowest-friction option and only escalating when actually blocked. Every request starts direct (no proxy); if Quora blocks it, the Actor automatically retries through a datacenter proxy, and if that's also blocked, through a residential proxy — sticking with residential for the rest of the run once it's needed. Each target keeps one sticky residential exit IP across its own requests so session cookies stay valid, and rotates to a fresh IP on retry. A response is only accepted once it's validated to actually contain the expected content block (question, user, topic, or tribe data) — a 200-status challenge page that merely looks successful is rejected and retried, rather than being treated as real data. If the whole proxy ladder is exhausted without a clean response, the Actor rotates through up to 6 additional fresh residential exit IPs with a short exponential backoff between attempts before giving up on that page. If a page is still hard-blocked after all of that, and useBrowserFallback is on (the default), it's re-rendered in a real headless Chromium browser — rotating proxies again at the browser-context level — as a last resort.

Does Quora Scraper return both relative and absolute answer dates?

Yes. Every answer row carries answer_timestamp (Quora's own relative string, e.g. "3y") and answer_created_at (the same moment as an absolute ISO-8601 UTC timestamp, e.g. "2022-06-14T07:46:04+00:00"). If Quora's underlying creationTime field is missing for a given answer, answer_created_at comes back as null rather than a guessed value.

How many results does Quora Scraper return per query?

Up to maxResults per search keyword (default 50, maximum 50,000), and the same maxResults value also caps how many answers are collected per question URL — it's one shared limit, not two separate ones. There's no separate hard-coded platform limit enforced in the Actor beyond that input ceiling; how many results actually come back also depends on how many matching pages the keyword search resolves and how many answers a given question genuinely has.

Why did my keyword search return zero results?

Keyword-to-URL resolution goes through a general-purpose search engine (a site:quora.com search), not Quora's own internal search — so a zero-result run usually means that search step got rate-limited on the exit IP in use, not that Quora has no matching content. The Actor already retries each search results page up to 3 times with a short backoff before giving up on it, and walks the same direct-to-residential proxy ladder used for Quora pages while doing so; if every attempt still comes back empty, the log will show the search engine didn't return results for that keyword. Re-running the job, or switching proxyConfiguration to force a residential proxy from the start, resolves most cases; direct URLs in directUrls bypass this step entirely and are unaffected by it.

How do I use Quora Scraper to monitor Quora activity over time?

Run the same question, profile, or keyword set on a recurring Apify Schedule, keep each run's dataset, and diff answer_count, follow_count, upvotes, comments_count and follower_count against the previous run. A jump in any of those between two runs is the signal — see "How do you monitor Quora activity over time?" above for the full workflow.

Does Quora Scraper work with Claude, ChatGPT, and AI agent frameworks?

Quora Scraper isn't published as an MCP tool, but it's fully callable as a standard HTTP endpoint through the Apify API from any agent framework that can make a web request — LangChain, LlamaIndex, a custom tool-calling loop, or a direct API call from inside a Claude or GPT-based agent. That lets an agent issue a query, get back real Quora answers as structured JSON, and ground its response in them instead of relying on the model's own memory of what Quora "probably" says.

How does Quora Scraper compare to other Quora scrapers on Apify?

All three of the highest-ranked competing Quora Actors on the Apify Store were checked on 2026-07-25. Quora Scraper Pro (botflowtech/quora-scraper-pro) also covers all five content types and AI-answer flagging, and its listing advertises pricing starting "from $5.00 / 1,000 results" — a figure from its own listing, not measured here — but its documented answer output shows only a relative answerDate string, with no absolute timestamp field. oneary/quora-scraper's published output is a generic four-field page scrape (url, title, description, textContent) with no dedicated answer, profile, topic or Space fields. memo23/Quora-Scraper-with-optional-login requires you to export and paste your own Quora account cookies to access search results at all, per its own README — Quora Scraper needs no login or cookies for any of the five content types it returns.

Can I limit a run to only one content type, like answers or profiles?

Not through the input schema — there is no contentTypes filter parameter. Quora Scraper returns whatever content type each search result or direct URL resolves to (question, answer, profile, topic, or Space), and you separate them afterward using the content_type field on every row, or by opening the matching pre-built dataset view (Questions, Answers, Profiles, Topics, Spaces) in the Apify Console. To scrape only answers in practice, paste question URLs directly into directUrls — each question URL yields one question row plus its answer rows, with no profile, topic, or Space rows mixed in.

What happens if a page is still blocked and useBrowserFallback is off?

The Actor gives up on that one URL and moves on — it does not push a row for it, and because nothing is pushed, nothing is charged. With useBrowserFallback at its default true, that same page gets one more attempt through a real headless browser before the Actor gives up on it; turning the setting off trades that safety net for a run that never launches a browser, which is faster and cheaper per attempt but slightly more likely to leave a hard-blocked page unscraped.

Can I use Quora Scraper without managing proxies or a Quora account?

Yes to both. Apify Proxy is built in and auto-escalates from direct to datacenter to residential only as needed, so you don't have to configure or pay for proxy tiers you don't end up using, and no Quora account, login, or cookie is required for any of the five content types — you only need an Apify account to run the Actor.

💬 Your feedback

Found a bug, hit an edge case, or need a field that isn't in the output yet? Open an issue from the Actor's page in the Apify Console, or reach out through Scrapier's Apify Store profile — reports like these directly shape what gets fixed and added next.