Developed within NFDIxCS

Extract insights from PDFs
with LLMs in Zotero

ZotExtract is a Zotero 7-9 plugin that lets you query large language models about your research PDFs. Run local LLMs for full privacy or connect to online providers.

Download Latest Release View on GitHub

Features

Everything you need to leverage LLMs for your research workflow — right inside Zotero.

📄

Session Context Extraction

Use Zotero metadata, abstracts, and indexed PDF full text by default inside paper-focused extraction sessions.

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Session Matrix

Review papers as columns and extraction questions as rows, with horizontal scrolling and persisted resize controls.

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Add Extractions

Choose whole question sets or individual questions in a three-column workflow that stays out of Settings.

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Privacy-First

Run local LLMs (Ollama, LM Studio, etc.) for complete data privacy. API keys stay in your local Zotero profile.

📝

Session Exports

Export XLSX, CSV, TSV, JSON, Markdown, and HTML from completed sessions without raw PDF full text or item-context export clutter.

⚙️

Flexible Configuration

Connect any OpenAI-compatible API. Configure model, base URL, context window, request timeout, and prompt templates.

Get Started in Minutes

Install the plugin, configure your LLM provider, and start extracting insights.

1

Download

Grab the latest .xpi file from the Releases page on GitHub.

2

Install

In Zotero 7, 8, or 9, go to Tools → Add-ons, click the gear icon, and choose Install Add-on From File.

3

Configure

Open Settings → ZotExtract and enter your API base URL, model, and key. Or point to a local Ollama server.

4

Extract

Right-click selected items or a collection, start a ZotExtract session, pick extractions, and export reviewed results.

Works With Your Favourite LLM

Connect to any OpenAI-compatible API — cloud or local.

OpenAI
Ollama
LM Studio
Any OpenAI-compatible API

Funding & Acknowledgements

ZotExtract is developed at the Chair of Information Science, University of Regensburg, as part of NFDIxCS — the National Research Data Infrastructure for and with Computer Science (NFDI×CS). NFDIxCS promotes the implementation of FAIR Data Principles for computer-science research data and software artefacts.

NFDIxCS is funded by the German Research Foundation (DFG) under the National Research Data Infrastructure (NFDI) programme.

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Developed at University of Regensburg — Chair of Information Science Contact: Samy Ateia
NFDIxCS operated by Gesellschaft für Informatik e.V. Consortium led by University of Duisburg-Essen