🎓 Academic Paper Search — Scholar Alternative (OpenAlex)

Academic Paper Search is a NexGenData tool on Apify that returns papers with citation counts, authors, venues, DOIs and open-access links from the OpenAlex index (about 250M works).

Search roughly 250 million academic works — journal articles, conference papers, books and arXiv preprints — by keyword and get clean JSON with title, abstract, year, authors, venue, citation count, DOI and open-access PDF link. The data comes from the OpenAlex API (open, no key), with Semantic Scholar as an automatic fallback. This actor does not scrape Google Scholar and does not need a login, a key or a proxy.

Use it to research academic literature and collect papers in bulk — output is paper metadata (16 fields per row).

What You Get

One row per paper:

Field	What it is
title, abstract	Title and abstract (abstract up to 1,000 characters; empty when the source has none)
year, publicationDate	Publication year and full date where known
authors, authorCount	Up to 10 author names, plus the total author count
venue	Journal, conference or publisher series
citationCount, referenceCount	Times cited, and number of works it cites
influentialCitations	Semantic Scholar's "influential citations" — filled only on the Semantic Scholar fallback, otherwise null
url, doi, openAccessPdf	DOI link (or OpenAlex page), bare DOI, and a free full-text link when one exists
arxivId	arXiv identifier when the paper has an arXiv version
paperId, source	Source record id and which source answered (openalex.org or semanticscholar.org)

Not included: author profiles, h-index, "cited by" lists, institution pages. This is a keyword search over works, nothing more.

Input

Field	Type	Default	Meaning
query	string	machine learning	Search words. Matched against title, abstract and full-text index on OpenAlex.
maxResults	integer	25	How many papers to return (1–500).
year	string	empty	Restrict to one publication year, e.g. 2024.

How it works

1. OpenAlex works?search= is queried in pages of up to 50 until maxResults is reached (polite pool, identified by e-mail, no key).
2. If OpenAlex returns nothing or errors, the same query goes to Semantic Scholar's paper search; HTTP 429 there is retried with backoff.
3. Every delivered row is charged once as it is written. If both sources fail and nothing is delivered, the run ends FAILED with the reason in the status message — it never reports success with an empty dataset.

Quick Start

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/google-scholar-scraper").call(run_input={
    "query": "transformer attention mechanism",
    "maxResults": 100,
    "year": "2024"
})
for paper in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(paper["title"], paper["citationCount"], paper["year"])

Pricing

Pay-per-event — no monthly minimum:

• Actor Start: $0.0005 per run
• Academic paper: $0.04 per paper delivered

100 papers cost $4.00. No charge for papers that are not delivered.

Use Cases

• Literature review — pull the top 200 papers on a topic into a CSV for screening
• Grant-writing prep — find the most-cited recent papers in a funding area (sort the citationCount column)
• Due diligence — check the publication record behind a deep-tech claim by searching the topic and the founder's name
• RAG / AI agents — feed abstracts, DOIs and open-access links into a retrieval pipeline

Related NexGenData Actors

Use case	Actor
AI-callable academic research for LLM agents	Academic Research MCP Server
NIH RePORTER grant + funding lookup	NIH RePORTER Grants Scraper
PubMed biomedical paper search	PubMed Research Search
News + press release tracking for AI agents	News MCP Server

FAQ

Q: Does this scrape Google Scholar? No. Google Scholar has no API and blocks automated access; this actor reads OpenAlex (and Semantic Scholar as fallback), which cover a very similar set of papers with open licences.

Q: Why are some abstracts empty? OpenAlex only has abstracts where the publisher shares them. Citation counts and links are still returned.

Q: Can I search by author or institution? Not as separate modes. Putting an author's name in query works for distinctive names.

Q: How fresh is the data? OpenAlex updates continuously; new works usually appear within days of publication.

Q: Can I schedule daily / weekly runs? Yes — built-in Apify Schedules with cron, plus webhooks on dataset write.

About NexGenData

NexGenData publishes 260+ buyer-intent actors covering SEC filings, YC alumni, academic research, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, and MCP servers for AI agents. All pay-per-result. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b

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How NexGenData Pricing Works

Every NexGenData actor uses pay-per-event pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills.

• Actor Start: a single-event charge each time you spin the actor up (scaled to memory size)
• Result: charged per item written to the default dataset
• No charge for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform

If you only need the data once a quarter, you only pay once a quarter. If you scale to millions of records, the unit cost stays the same.

Apify Platform Bonus

New to Apify? Sign up with the NexGenData referral link — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet.

Integration Surface

Every actor in the NexGenData catalog can be triggered from:

• Apify console — point-and-click run
• Apify API — REST + webhooks
• Apify Python / JS SDKs — programmatic batch
• Zapier, Make.com, n8n — official integrations
• MCP — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents
• Schedules — built-in cron for daily / weekly / monthly runs
• Webhooks — POST results to any HTTPS endpoint on dataset write

Support

NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version.

📦 Full catalog: apify.com/nexgendata

🤖 Use with AI agents

Structured JSON for LLM and agent pipelines (Claude, the OpenAI Agents SDK, n8n or any MCP-aware client).

Sample agent prompt:

Find 2025 papers on retrieval-augmented generation with citation counts.