Preprints.ai
Integration

API

Integrate preprint quality grades into your platform, journal workflow, or LLM pipeline.

Quick start

curl https://preprints.ai/v1/pipeline | jq '.assessments[0]'

No key required. Rate-limited at 120 requests per minute per IP.

Fetching a specific paper

# By DOI
curl https://preprints.ai/reviews/10.1101/2025.01.15.633214

# Trigger assessment if not cached
curl -X POST https://preprints.ai/v1/assess \
  -H "content-type: application/json" \
  -d '{"doi": "10.1101/2025.01.15.633214"}'

Python

import httpx

def get_grade(doi: str) -> dict:
    r = httpx.get(f"https://preprints.ai/reviews/{doi}")
    r.raise_for_status()
    return r.json()

grade = get_grade("10.1101/2025.01.15.633214")
print(grade["assessment"]["grade"])  # e.g. "B3"

JavaScript

async function getGrade(doi) {
  const r = await fetch(`https://preprints.ai/reviews/${encodeURIComponent(doi)}`);
  if (!r.ok) throw new Error(r.statusText);
  return r.json();
}

const { assessment } = await getGrade("10.1101/2025.01.15.633214");
console.log(assessment.grade);  // "B3"

Displaying a grade badge

Every assessment has a shareable badge. See embed badges for the SVG image URLs that update in real time.

<img src="https://preprints.ai/badge/10.1101/2025.01.15.633214" alt="Preprints.ai grade">

RSS feed

Subscribe to new assessments as they land:

<link rel="alternate" type="application/rss+xml" href="https://preprints.ai/feed.xml">

Partner integrations

If you're a journal, preprint server, or aggregator wanting to ingest assessments at scale, contact us — we offer:

See also