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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

Peer-reviewed paper discovery and evidence validation

AI-powered academic search engine with Consensus Meter and Deep Search across 250M+ peer-reviewed papers. MCP server for Claude and ChatGPT. Free; Pro $12/mo; Deep $45/mo.

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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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Some agents in this stack expose an MCP server

MCP (Model Context Protocol) is an open standard for connecting AI agents to tools and data. The agents that publish a server can be connected into directly by an AI assistant. The others act as clients, meaning they consume external tools rather than exposing their own, so those steps still need conventional integration.

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