consensus.app

# Consensus > Consensus is an AI-powered scientific search engine that finds, ranks, and synthesizes peer-reviewed research, returning evidence-backed answers with inline citations. Consensus helps researchers, clinicians, students, journalists, and AI agents answer questions from the academic literature. We index over 200 million peer-reviewed papers from Semantic Scholar, OpenAlex, PubMed, and publisher feeds, then rank results by relevance, study design, citation count, and journal quality. Every claim links back to its source paper. For deeper context (workflows, auth, full tier table, competitive comparisons), see [llms-full.txt](https://consensus.app/llms-full.txt). ## Use cases - **Find peer-reviewed papers** on a specific research question ("does intermittent fasting improve cardiovascular health?") - **Summarize the consensus** across studies on a topic ("what does the literature say about caffeine and endurance performance?") - **Identify high-quality evidence** (systematic reviews, meta-analyses, RCTs) for a clinical or policy question - **Compare findings** across study designs, populations, or interventions - **Power agent workflows** that need citable scientific sources via the REST API or MCP server ## Constraints - **Corpus**: academic literature from Semantic Scholar, OpenAlex, and PubMed. Preprints are included by default and tagged in results; pass `exclude_preprints=true` (MCP) or `excludePreprints=true` (REST API) to filter to peer-reviewed papers only. - **Languages**: primarily English. Non-English papers are indexed where metadata is available, but search ranking and AI summarization are optimized for English. - **Freshness**: the index is updated continuously, but papers published in the last few weeks may not yet be present. - **Access tiers**: anonymous (limited), Free, Pro, Team, and Enterprise. See [pricing](https://consensus.app/pricing) for current rate limits and quotas. - **Output**: AI summaries are faithful to source papers