openalex-paper-search
Academic Paper Search (OpenAlex)
Search 240M+ scholarly works using the OpenAlex API -- completely free, no API key required, no SDK needed. Just curl or bash with URL construction.
Full docs: https://docs.openalex.org
Quick Start
OpenAlex is a REST API. You query it by constructing URLs and fetching them with curl. All responses are JSON.
# Search for papers about "transformer architecture"
curl -s "https://api.openalex.org/works?search=transformer+architecture&per_page=5&mailto=agent@kortix.ai" | python3 -m json.tool
Important: Always include mailto=agent@kortix.ai (or any valid email) in every request. Without it, you're limited to 1 request/second. With it, you get 10 requests/second (the "polite pool").
Core Concepts
Entities
OpenAlex has these entity types (all queryable):
| Entity | Endpoint | Count | Description |
|---|---|---|---|
| Works | /works |
240M+ | Papers, articles, books, datasets, theses |
| Authors | /authors |
90M+ | People who create works |
| Sources | /sources |
250K+ | Journals, repositories, conferences |
| Institutions | /institutions |
110K+ | Universities, research orgs |
| Topics | /topics |
4K+ | Research topics (hierarchical) |
Work Object -- Key Fields
When you fetch a work, these are the most useful fields:
id OpenAlex ID (e.g., "https://openalex.org/W2741809807")
doi DOI URL
title / display_name Paper title
publication_year Year published
publication_date Full date (YYYY-MM-DD)
cited_by_count Number of incoming citations
fwci Field-Weighted Citation Impact (normalized)
type article, preprint, review, book, dataset, etc.
language ISO 639-1 code (e.g., "en")
is_retracted Boolean
open_access.is_oa Boolean -- is it freely accessible?
open_access.oa_url Direct URL to free version
authorships List of authors with names, institutions, ORCIDs
abstract_inverted_index Abstract as inverted index (needs reconstruction)
referenced_works List of OpenAlex IDs this work cites (outgoing)
related_works Algorithmically related works
cited_by_api_url API URL to get works that cite this one (incoming)
topics Assigned research topics with scores
keywords Extracted keywords with scores
primary_location Where the work is published (journal, repo)
best_oa_location Best open access location with PDF link
Reconstructing Abstracts
OpenAlex stores abstracts as inverted indexes for legal reasons. To get plaintext, reconstruct:
import json, sys
# Read the abstract_inverted_index from a work object
inv_idx = work["abstract_inverted_index"]
if inv_idx:
words = [""] * (max(max(positions) for positions in inv_idx.values()) + 1)
for word, positions in inv_idx.items():
for pos in positions:
words[pos] = word
abstract = " ".join(words)
Or in bash with python3 -c:
# Pipe a work JSON into this to extract the abstract
echo "$WORK_JSON" | python3 -c "
import json,sys
w=json.load(sys.stdin)
idx=w.get('abstract_inverted_index',{})
if idx:
words=['']*( max(max(p) for p in idx.values())+1 )
for word,positions in idx.items():
for pos in positions: words[pos]=word
print(' '.join(words))
"
Searching for Papers
Basic Keyword Search
Searches across titles, abstracts, and fulltext. Uses stemming and stop-word removal.
# Simple search
curl -s "https://api.openalex.org/works?search=large+language+models&mailto=agent@kortix.ai"
# With per_page limit
curl -s "https://api.openalex.org/works?search=CRISPR+gene+editing&per_page=10&mailto=agent@kortix.ai"
Boolean Search
Use uppercase AND, OR, NOT with parentheses and quoted phrases:
# Complex boolean query
curl -s "https://api.openalex.org/works?search=(reinforcement+learning+AND+%22robot+control%22)+NOT+simulation&mailto=agent@kortix.ai"
# Exact phrase match (use double quotes, URL-encoded as %22)
curl -s "https://api.openalex.org/works?search=%22attention+is+all+you+need%22&mailto=agent@kortix.ai"
Search Specific Fields
# Title only
curl -s "https://api.openalex.org/works?filter=title.search:transformer&mailto=agent@kortix.ai"
# Abstract only
curl -s "https://api.openalex.org/works?filter=abstract.search:protein+folding&mailto=agent@kortix.ai"
# Title and abstract combined
curl -s "https://api.openalex.org/works?filter=title_and_abstract.search:neural+scaling+laws&mailto=agent@kortix.ai"
# Fulltext search (subset of works)
curl -s "https://api.openalex.org/works?filter=fulltext.search:climate+tipping+points&mailto=agent@kortix.ai"
Filtering
Filters are the most powerful feature. Combine them with commas (AND) or pipes (OR).
Most Useful Filters
# By publication year
?filter=publication_year:2024
?filter=publication_year:2020-2024
?filter=publication_year:>2022
# By citation count
?filter=cited_by_count:>100 # highly cited
?filter=cited_by_count:>1000 # landmark papers
# By open access
?filter=is_oa:true # only open access
?filter=oa_status:gold # gold OA only
# By type
?filter=type:article # journal articles
?filter=type:preprint # preprints
?filter=type:review # review articles
# By language
?filter=language:en # English only
# Not retracted
?filter=is_retracted:false
# Has abstract
?filter=has_abstract:true
# Has downloadable PDF
?filter=has_content.pdf:true
# By author (OpenAlex ID)
?filter=author.id:A5023888391
# By institution (OpenAlex ID)
?filter=institutions.id:I27837315 # e.g., University of Michigan
# By DOI
?filter=doi:https://doi.org/10.1038/s41586-021-03819-2
# By indexed source
?filter=indexed_in:arxiv # arXiv papers
?filter=indexed_in:pubmed # PubMed papers
?filter=indexed_in:crossref # Crossref papers
Combining Filters
# AND: comma-separated
?filter=publication_year:>2022,cited_by_count:>50,is_oa:true,type:article
# OR: pipe-separated within a filter
?filter=publication_year:2023|2024
# NOT: prefix with !
?filter=type:!preprint
# Combined example: highly-cited OA articles from 2023-2024, not preprints
curl -s "https://api.openalex.org/works?filter=publication_year:2023-2024,cited_by_count:>50,is_oa:true,type:!preprint&search=machine+learning&per_page=10&mailto=agent@kortix.ai"
Sorting
# Most cited first
?sort=cited_by_count:desc
# Most recent first
?sort=publication_date:desc
# Most relevant first (only when using search)
?sort=relevance_score:desc
# Multiple sort keys
?sort=publication_year:desc,cited_by_count:desc
Pagination
Two modes: basic paging (for browsing) and cursor paging (for collecting all results).
# Basic paging (limited to 10,000 results)
?page=1&per_page=25
?page=2&per_page=25
# Cursor paging (unlimited, for collecting everything)
?per_page=100&cursor=* # first page
?per_page=100&cursor=IlsxNjk0ODc... # next page (cursor from previous response meta)
The cursor for the next page is in response.meta.next_cursor. When it's null, you've reached the end.
Select Fields
Reduce response size by selecting only the fields you need:
# Only get IDs, titles, citation counts, and DOIs
?select=id,display_name,cited_by_count,doi,publication_year
# Minimal metadata for scanning
?select=id,display_name,publication_year,cited_by_count,open_access
Citation Graph Traversal
Find what a paper cites (outgoing references)
# Get works cited BY a specific paper
curl -s "https://api.openalex.org/works?filter=cited_by:W2741809807&per_page=25&mailto=agent@kortix.ai"
Find what cites a paper (incoming citations)
# Get works that CITE a specific paper
curl -s "https://api.openalex.org/works?filter=cites:W2741809807&sort=cited_by_count:desc&per_page=25&mailto=agent@kortix.ai"
Find related works
# Get related works (algorithmic, based on shared concepts)
curl -s "https://api.openalex.org/works?filter=related_to:W2741809807&per_page=25&mailto=agent@kortix.ai"
Citation chain: follow the references
- Get a seminal paper by DOI
- Find its
referenced_works(what it cites) - Find who cites it (
filter=cites:WORK_ID) - For the most cited citers, repeat
This is how you build a literature graph around a topic.
Author Lookup
# Search for an author
curl -s "https://api.openalex.org/authors?search=Yann+LeCun&mailto=agent@kortix.ai"
# Get an author's works (by OpenAlex author ID)
curl -s "https://api.openalex.org/works?filter=author.id:A5064850633&sort=cited_by_count:desc&per_page=10&mailto=agent@kortix.ai"
# Get an author by ORCID
curl -s "https://api.openalex.org/authors/orcid:0000-0001-6187-6610?mailto=agent@kortix.ai"
Lookup by External ID
# By DOI
curl -s "https://api.openalex.org/works/doi:10.1038/s41586-021-03819-2?mailto=agent@kortix.ai"
# By PubMed ID
curl -s "https://api.openalex.org/works/pmid:14907713?mailto=agent@kortix.ai"
# By arXiv ID (via DOI)
curl -s "https://api.openalex.org/works/doi:10.48550/arXiv.2303.08774?mailto=agent@kortix.ai"
# Batch lookup: up to 50 IDs at once
curl -s "https://api.openalex.org/works?filter=doi:https://doi.org/10.1234/a|https://doi.org/10.1234/b|https://doi.org/10.1234/c&mailto=agent@kortix.ai"
Open Access & PDF Access
# Find OA papers with direct PDF links
curl -s "https://api.openalex.org/works?search=quantum+computing&filter=is_oa:true,has_content.pdf:true&select=id,display_name,open_access,best_oa_location&per_page=5&mailto=agent@kortix.ai"
The best_oa_location.pdf_url field gives a direct PDF link when available. The open_access.oa_url gives the best available OA landing page or PDF.
Practical Workflows
Literature Survey on a Topic
# 1. Find the most-cited papers on a topic
curl -s "https://api.openalex.org/works?search=retrieval+augmented+generation&sort=cited_by_count:desc&filter=publication_year:>2020,type:article,has_abstract:true&per_page=20&select=id,display_name,publication_year,cited_by_count,doi,authorships,abstract_inverted_index&mailto=agent@kortix.ai"
# 2. For the top papers, explore their citation graphs
curl -s "https://api.openalex.org/works?filter=cites:W4285719527&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&mailto=agent@kortix.ai"
# 3. Find recent papers building on this work
curl -s "https://api.openalex.org/works?filter=cites:W4285719527,publication_year:>2023&sort=publication_date:desc&per_page=10&mailto=agent@kortix.ai"
Find Landmark/Seminal Papers
# Highly cited + search term
curl -s "https://api.openalex.org/works?search=attention+mechanism+neural+networks&filter=cited_by_count:>500,type:article&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&mailto=agent@kortix.ai"
Find Recent Preprints
# Latest preprints on a topic
curl -s "https://api.openalex.org/works?search=multimodal+large+language+models&filter=type:preprint,publication_year:2025&sort=publication_date:desc&per_page=15&mailto=agent@kortix.ai"
Find Review Articles
# Review/survey papers on a topic
curl -s "https://api.openalex.org/works?search=federated+learning&filter=type:review,cited_by_count:>20&sort=cited_by_count:desc&per_page=10&mailto=agent@kortix.ai"
Author Analysis
# 1. Find the author
curl -s "https://api.openalex.org/authors?search=Geoffrey+Hinton&select=id,display_name,works_count,cited_by_count,last_known_institutions&mailto=agent@kortix.ai"
# 2. Get their most influential papers
curl -s "https://api.openalex.org/works?filter=author.id:A5068082743&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&mailto=agent@kortix.ai"
# 3. Get their recent work
curl -s "https://api.openalex.org/works?filter=author.id:A5068082743,publication_year:>2023&sort=publication_date:desc&per_page=10&mailto=agent@kortix.ai"
Saving Results to Disk
When doing deep research, save paper data to disk for later processing:
# Save search results as JSON
curl -s "https://api.openalex.org/works?search=topic&per_page=50&mailto=agent@kortix.ai" > research/papers/topic-search.json
# Extract and save a clean summary
curl -s "https://api.openalex.org/works?search=topic&per_page=50&select=id,display_name,publication_year,cited_by_count,doi,authorships&mailto=agent@kortix.ai" | python3 -c "
import json, sys
data = json.load(sys.stdin)
for w in data.get('results', []):
authors = ', '.join(a['author']['display_name'] for a in w.get('authorships', [])[:3])
if len(w.get('authorships', [])) > 3: authors += ' et al.'
print(f\"[{w.get('cited_by_count',0)} cites] {w['display_name']} ({w.get('publication_year','?')}) - {authors}\")
if w.get('doi'): print(f\" DOI: {w['doi']}\")
print()
" > research/papers/topic-summary.txt
For deep research, save individual paper metadata to your sources-index.md and raw data to sources/:
# Save a paper's full metadata
curl -s "https://api.openalex.org/works/W2741809807?mailto=agent@kortix.ai" > research/sources/001-paper-title.json
Rate Limits
| Pool | Rate | How to get it |
|---|---|---|
| Common | 1 req/sec | No email provided |
| Polite | 10 req/sec | Add mailto=your@email.com to requests |
| Premium | Higher | Paid API key via api_key param |
Always use the polite pool. Add &mailto=agent@kortix.ai to every request.
Tips
- Use
selectaggressively to reduce response size and speed up requests - Use
per_page=100(max) when collecting lots of results to minimize request count - Use cursor paging (
cursor=*) when you need more than 10,000 results - Batch DOI lookups with OR syntax:
filter=doi:DOI1|DOI2|DOI3(up to 50) - Reconstruct abstracts using the inverted index -- don't skip this, abstracts are gold
- Follow citation chains to find seminal works and recent developments
- Filter by
has_abstract:truewhen you need abstracts (not all works have them) - Filter by
indexed_in:arxivorindexed_in:pubmedto target specific repositories - Sort by
cited_by_count:descto find the most influential papers first - Combine search + filters for precise results: search gives relevance, filters give precision