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PapersGPT for Zotero

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papersgpt

A powerful Zotero AI and MCP plugin with ChatGPT, Gemini 3.7, Claude Fable 5, Claude Opus 5, DeepSeek V4, Grok, OpenRouter, Kimi k3, GLM 5.3, SiliconFlow, GPT-oss, Gemma 4, Qwen 3.8

Publisherpapersgpt
Repositorypapersgpt-for-zotero
LanguageJavaScript
Forks
96
Stars
2.6K
Available tools
0
Transport typestdio
Categories
LicenseAGPL-3.0
Links
  • Connect tools to AI workflows

    PapersGPT for Zotero exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    2.6K stars and 96 forks from the linked repository.

PapersGPT

Industrial-Scale Multi-Document Intelligence for Zotero. 100% Local. Zero Hallucinations.

PapersGPT is a professional-grade Zotero extension engineered in Native C++ to transform thousands of isolated PDFs into a single, high-precision knowledge engine. While standard tools struggle with single-file chat or slow, "fuzzy" embeddings, PapersGPT delivers instant, cross-document synthesis and global library search with absolute data sovereignty.


⚡ Extreme Performance: Built for "Big Data" Researchers

Stop waiting for embedding progress bars. Most AI tools use Python/JS scripts that lag or crash as your library grows. PapersGPT is built to handle professional-scale research. It turns massive document silos into instant knowledge bases. Whether you have 100 or 10,000+ PDFs, the experience remains lightning-fast. PapersGPT’s Enterprise-Grade Performance:

  • Massive Throughput: 10,000 PDFs (170k pages) totaling 42GB indexed in just 7 minutes.
  • Instant Retrieval: Average query response time of 19.5ms, even at 10k scale (42GB of knowledge).
  • Smart Resource Management: Automatic memory offloading ensures a low resource footprint for large-scale enterprise libraries.
Library SizeRaw Data SizeIndexing TimeAvg. Query TimeMemory (RSS)Index Size
1,000 PDFs4.2 GB51.5s13.1 ms353 MB100 MB
10,000 PDFs42 GB421s (7m 01s)19.5 ms2.21 GB901 MB

👉 View Detailed Scalability Report & System Specs

  • Hardware Efficiency: Millisecond-level retrieval with minimal RAM usage, leaving your system resources free for other tasks.
  • Zero-Cloud Dependency: High-speed structural indexing occurs 100% on your machine. No external APIs, no cloud bottlenecks, even works in Airplane Mode.

🎯 Superior Multi-Doc Intelligence & Accuracy

PapersGPT moves beyond the "fuzzy" matching of standard semantic search by embeddings. Our engine understands document structure, ensuring that cross-paper comparisons are logically sound and factually accurate.

  • Deep Cross-Document Comparison
    “Compare the sample sizes and p-values of all 50 clinical trials in my 'Cardiology' folder.”
    AI synthesizes data from multiple files into structured tables or reports without losing the nuances of individual studies.

  • Global Library Synthesis
    Ask questions across your entire Zotero library. Identify trends, evolution of terms, or conflicting evidence across 10,000+ documents simultaneously.

  • Verifiable Evidence (Click-to-Jump)
    Accuracy is useless without proof. Every synthesis includes interactive citations. Every AI response includes precise citations; clicking on them takes you directly to the specific paper being cited.

  • Ensure the absolute 100% privacy and security of your local sensitive Zotero data

  • Support 100% offline local LLMs
    PapersGPT currently supports three different ways to connect to local large language models (LLMs):

    1. Integrated SOTA open-source LLMs – such as Gemma 4 12B and Qwen3.5 4B. These models can be downloaded and run with a single click, eliminating the need for complex installation procedures; simply selecting a model from the "Local LLM" option triggers an automatic download from Hugging Face and launches the model.

    2. Custom OpenAI-compatible endpoint – connect to a flexible OpenAI-compatible privately deployed LLM endpoint by configuring a customized LLM API within PapersGPT.

    3. Ollama integration – supports connections to local Ollama instances; any LLM deployed and running locally via Ollama can be connected and used simply by configuring it within PapersGPT.

  • Parsing, Indexing and Searching documents in Zotero are performed locally, there is no reliance on the clouds, and these operations can be run offline.

  • Local LLMs and local document processing ensure "zero-byte" data leakage from your device.


✨ Core Unique Features

  • AutoPilot Automation: The world's first "Autonomous Researcher" for Zotero. Define a research goal and let AI batch-process 1,000+ papers overnight, saving insights directly into Zotero Notes while you sleep.
  • SOTA Model Cowork: Seamlessly switch between DeepSeek V4 Pro, Claude Fable 5, Claude Opus 5, GPT-5.6, Gemini 3.7 Flash, GLM 5.3, and Kimi k3, or run Free Local LLMs (via Ollama) for a total air-gapped experience.
  • Zotero MCP Server: Integrate your local Zotero knowledge base as a primary "skill" for agentic platforms like Claude Code, Cursor, or Windsurf. Even no need to start Zotero, you can index and search all your Zotero library very fast by the mcp-zotero.

📖 Quickstart

Step 1: Download and Install

  1. First, download the latest PapersGPT.
  2. Then, install the downloaded Zotero plugin file. For more details, please see here.

Step 2: Start Chatting with a PDF, Multiple PDFs or your entire Zotero Library

1. Launch PapersGPT

  • Chat with a Single PDF

    • Open a PDF from your Zotero library.
    • When you need AI assistance, click on the top menu of the PDF viewer or use a keyboard shortcut:
      • macOS: Command + Enter
      • Windows: Ctrl + Enter
  • Chat with Multiple PDFs

    • Select multiple files or a collection in the main Zotero window. Hold Ctrl while clicking files on Windows. Hold Command while clicking files on Mac.
  • Chat with the entire Zotero Library

    • Simply check "Search entire library" in PapersGPT, and it will search the entire document library for relevant documents and synthesize answers based on the questions.

2. Select a LLM model and configure the API KEY of the model

For more detailed information please see here.

3. Ask Questions

  • Use the built-in prompts for common tasks like: Summary, Background, Generating a literature review, Theoretical frameworks, Future directions.
  • You can also directly type any question or custom prompt to start the conversation.

Step 3: Manage Your Findings and close the chat

  • After chatting, you can easily save the key insights and answers you've gathered from the conversation.
  • When you're finished, click the red cross (X) close button to exit the PapersGPT window.

🔌 MCP & SKILL Support

Support MCP which makes you can access your Zotero papers in Claude, ChatGPT desktop app, please see here in detail.

Professional SKILL provides various agents for connecting to your local Zotero library.

If you use OpenClaw, you can see the papersgpt-for-zotero skill here. You are welcome to submit any issues in this github repo or clawhub.

If you use the App of OpenAI, Claude, Cursor, Claude Code, CodeX or Gemini CLI, you can directly copy and load the SKILL.


🏢 Professional Compliance

PapersGPT is designed for professionals in Research, Legal and Finance who handle high-stakes, sensitive data:

  • Research: Cross-reference thousands of papers while maintaining 100% data sovereignty.
  • Finance: Synthesize decade-long 10-K filings without cloud risk.
  • Legal: Perform high-precision discovery across thousands of case files.

👥 Join 50,000+ Researchers

Unlock Professional Capabilities at papersgpt.com →

Don't just search your library. Understand it. PapersGPT provides the industrial-scale intelligence your research library demands.

Use PapersGPT for Zotero MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once PapersGPT for Zotero is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add PapersGPT for Zotero as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the PapersGPT for Zotero MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "papersgpt-for-zotero": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the PapersGPT for Zotero MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the PapersGPT for Zotero MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use PapersGPT for Zotero to help me with this task?
PapersGPT for Zotero
Sure. I read it.
Here is what I found using PapersGPT for Zotero.

Frequently asked questions

What is the PapersGPT for Zotero MCP server used for?

PapersGPT for Zotero is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use PapersGPT for Zotero MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use PapersGPT for Zotero with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use PapersGPT for Zotero MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With PapersGPT for Zotero connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect PapersGPT for Zotero MCP to TypingMind?

PapersGPT for Zotero runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does PapersGPT for Zotero MCP provide in TypingMind?

PapersGPT for Zotero exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use PapersGPT for Zotero MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If PapersGPT for Zotero requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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