The Consensus API is a REST API for searching academic literature: one call returns relevance-ranked, peer-reviewed papers from a corpus of 220M+, with citation counts, study metadata, journal quality signals, and query-relevant full-text excerpts.
It is the same search engine behind Consensus, used by millions of researchers every month.
curl -G "https://api.consensus.app/v1/search" \
-H "x-api-key: $CONSENSUS_API_KEY" \
--data-urlencode "query=Does creatine improve cognition?" \
--data-urlencode "year_min=2015" \
--data-urlencode "study_types=rct,meta-analysis"Python
import requests
resp = requests.get(
"https://api.consensus.app/v1/search",
headers={"x-api-key": "YOUR_API_KEY"},
params={
"query": "Does creatine improve cognition?",
"year_min": 2015,
"study_types": "rct,meta-analysis",
},
)
for paper in resp.json()["results"]:
print(paper["publish_year"], paper["citation_count"], paper["title"])JavaScript
const params = new URLSearchParams({
query: "Does creatine improve cognition?",
year_min: "2015",
study_types: "rct,meta-analysis",
});
const resp = await fetch(`https://api.consensus.app/v1/search?${params}`, {
headers: { "x-api-key": process.env.CONSENSUS_API_KEY },
});
const { results } = await resp.json();GET https://api.consensus.app/v1/search
Authenticate with your API key in the x-api-key header.
Migrating from
/v1/quick_search? It is deprecated and will be removed on 2027-02-07./v1/searchis the same contract: update the path and you are done. Details.
{
"results": [
{
"title": "The effects of creatine supplementation on cognitive performance: a randomised controlled study",
"authors": ["Sandkühler, J.F.", "..."],
"publish_year": 2023,
"doi": "10.1186/s12916-023-03146-5",
"journal_name": "BMC Medicine",
"citation_count": 47,
"study_type": "rct",
"sample_size": 123,
"sjr_best_quartile": 1,
"takeaway": "Creatine supplementation showed small positive effects on cognitive performance...",
"abstract": "...",
"url": "https://consensus.app/papers/..."
}
],
"page": 0,
"page_size": 20,
"is_end": false,
"next_page": 1
}Every result includes title, abstract, authors, DOI, journal, publication year, volume and pages, and citation count. Depending on the paper you also get study type, sample size, study count, population type (human or animal), preprint status, countries of study, institutions, influential citation count, and a plain-language key takeaway.
Two opt-in extras:
include_semantic_score=true: a relevance score for the top resultsinclude_full_text_chunks=true: query-relevant excerpts from licensed full text (paid plans)
| What you want | Parameters |
|---|---|
| A publication window | year_min, year_max, month_min, month_max |
| Specific study designs | study_types (rct, meta-analysis, systematic review, cohort study, ...) |
| Methodological rigor | human, controlled, sample_size_min, exclude_preprints |
| Journal quality | sjr_min / sjr_max (SJR quartile, 1 = top), citation_min |
| Medical focus | medical_mode (top medical journals and guidelines, ~8M documents), clinical_guideline |
| Scope | domain (med, bio, cs, psych, econ, ...), country, journal_name, publisher_name, open_access |
Full parameter reference: docs.consensus.app/reference/v1_search
The Consensus API is self-serve: create an API key from your Consensus account and start building. Paid plans (Pro, Deep, Teams) include monthly API usage. For production workloads, high volume, and custom rate limits, talk to us about Enterprise.
- LLM and RAG applications grounded in citable, peer-reviewed sources
- Literature discovery and systematic review tooling
- Research copilots, writing assistants, and reference managers
- Evidence dashboards for clinical and policy teams
Looking to use Consensus inside an AI assistant instead of your own code? The Consensus MCP server gives Claude, ChatGPT, Cursor, and any MCP client the same search over a remote connection:
https://mcp.consensus.app/mcp
See the consensus-mcp repo and the MCP guide.
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