Most AI research tools only read titles and abstracts. The answer you need is usually buried in the methods, results, or discussion. Consensus reads deeper: it analyzes the full text of papers, including paywalled articles from major publishers, to decide whether a paper actually answers your question and to ground its analysis in complete context.
Where full text comes from
Publisher partnerships
Publisher partnerships
Consensus has agreements with the publishers below to read the full text of paywalled papers for AI analysis inside Consensus, including 6 of the 12 largest publishers in the world.

























Open-access PDFs
Open-access PDFs
For any open-access paper, Consensus pulls the full PDF directly into the app. When the AI quotes from it, you can click straight to the passage in the PDF.
Your own uploads
Your own uploads
If a paper isn’t in the index, bring it. Upload PDFs directly or sync your Zotero library. Uploads stay private to your account and are analyzed with the same engine, including full-text search, snippet highlighting, and synthesis. See Library.
What about my institution’s subscriptions? Consensus connects to your university or institution’s library through LibKey, but only for link resolving: it gives you direct links to papers your library subscribes to. Consensus doesn’t use full text from LibKey. All the full text Consensus analyzes comes from the three sources above.
Where full text is used
- Retrieval. Your query is matched against titles, abstracts, and full text, which is one reason Consensus retrieval tests 10% more accurate than Google Scholar head to head.
- Pro and Deep analysis. Answers pull directly from full text when available. A checkmark on an in-line citation means the full text was used; no checkmark means the abstract was.
- Citation Grounding. Hover a citation to see the exact quote; click to open the paper at that passage. See Citation Grounding.
- Comparison tables. Side-by-side values for methods, sample sizes, findings, and limitations, pulled from the body of each paper.
- Chat with full text. Ask questions of one paper, a Collection, or your whole Library.
Analysis access and reading access are different. Consensus may use a paywalled paper’s full text to generate summaries and tables, but the article itself may remain behind the publisher’s paywall. Viewing or downloading it depends on your institutional or personal subscription.
Full text in the API and MCP. The Consensus API can return query-relevant full-text excerpts alongside each paper: pass
include_full_text_chunks=true and read the full_text_chunks field (see the /v1/search reference). The MCP server supports the same option in its search tool, so your assistant can quote the relevant passages directly. Both are available on all paid plans (Pro, Deep, Teams, and Enterprise).How to use it
1
Look for the checkmark
In any Pro or Deep answer, citations with a checkmark were analyzed from full text.
2
Jump to the passage
Hover a citation to see the supporting quote, then click Show in paper to open the PDF at the highlighted passage.

3
Chat with a paper
Click + in the search bar and select papers from your Library or upload new ones, tick papers in a results list, or ask from a paper’s details page. Chatting with full text runs in Pro or Deep mode.
4
Filter to open access
Use the Open access filter to see only papers whose full text is viewable.
5
Connect your institution
In Settings › Preferences, search for your institution to get LibKey links to papers your library subscribes to. This only changes where links take you, not what Consensus analyzes. If a paper is still paywalled, try your library portal directly.
Availability
Full text is used wherever it’s available, on every plan. Chatting with the full text of a paper, Collection, or Library requires a Pro or Deep message, which draws on your plan’s credits (see What is Consensus). On all paid plans, the API and MCP can also return full-text excerpts alongside each paper.Next
Library
Upload PDFs and import from Zotero.
Build a comparison table
A tutorial that leans on full text.