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Academic Research Stack

Consensus searches across 200 million peer-reviewed papers using AI to find studies that directly answer your research question, returning consensus meters showing whether the evidence supports a claim. Elicit then takes those papers further, extracting key data points, methods, and findings into structured summaries that can be compared across studies. Together they compress days of literature review into a focused, evidence-grounded research session.

The workflow — 2 agents in sequence

1
Consensus logo
ConsensusMCP server

Peer-reviewed paper discovery and evidence validation

Academic search engine drawing on 250M+ peer-reviewed papers, with a Consensus Meter showing where studies agree and Deep Search for literature reviews. Free tier, Pro from $12/mo billed annually (USD).

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Consensus finds relevant studies and returns consensus scores. Selected papers are imported into Elicit for deeper extraction

2
Elicit logo
ElicitMCP server

Structured data extraction and cross-study comparison

AI research assistant for systematic literature reviews across 138M papers and 545K clinical trials. MCP server, full API, SOC 2 certified. Free; Pro $49/mo annual. 5M+ researchers.

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Every agent in this stack exposes an MCP server

MCP (Model Context Protocol) is an open standard for connecting AI agents to tools and data. Because each agent here publishes its own MCP server, an assistant or orchestrator can connect into every step of this stack directly, without custom API glue.

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