productivity

Zotero

kujenga

by kujenga

Integrate Zotero with top citations tools. Search and manage scholarly references using software Zotero and zoterobib fo

Integrates with Zotero to enable searching libraries, retrieving metadata, and accessing full-text content for scholarly research workflows.

github stars

135

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Access existing Zotero libraryRequires Zotero API key setup

best for

  • / Researchers organizing academic papers
  • / Students managing citations and references
  • / Academics writing literature reviews

capabilities

  • / List Zotero collections and folders
  • / Search your research library
  • / Retrieve paper details and metadata
  • / Browse collection items
  • / Fetch recent publications

what it does

Connects to your Zotero research library to browse collections, search papers, and retrieve citation details. Works through Zotero's API to access your existing research database.

about

Zotero is a community-built MCP server published by kujenga that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Zotero with top citations tools. Search and manage scholarly references using software Zotero and zoterobib fo It is categorized under productivity.

how to install

You can install Zotero in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Zotero is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Model Context Protocol server for Zotero

GitHub branch status PyPI - Version

This project is a python server that implements the Model Context Protocol (MCP) for Zotero, giving you access to your Zotero library within AI assistants. It is intended to implement a small but maximally useful set of interactions with Zotero for use with MCP clients.

<a href="https://glama.ai/mcp/servers/jknz38ntu4"> <img width="380" height="200" src="https://glama.ai/mcp/servers/jknz38ntu4/badge" alt="Zotero Server MCP server" /> </a>

Features

This MCP server provides the following tools:

  • zotero_search_items: Search for items in your Zotero library using a text query
  • zotero_item_metadata: Get detailed metadata information about a specific Zotero item
  • zotero_item_fulltext: Get the full text of a specific Zotero item (i.e. PDF contents)

These can be discovered and accessed through any MCP client or through the MCP Inspector.

Each tool returns formatted text containing relevant information from your Zotero items, and AI assistants such as Claude can use them sequentially, searching for items then retrieving their metadata or text content.

Installation

This server can either run against either a local API offered by the Zotero desktop application) or through the Zotero Web API. The local API can be a bit more responsive, but requires that the Zotero app be running on the same computer with the API enabled. To enable the local API, do the following steps:

  1. Open Zotero and open "Zotero Settings"
  2. Under the "Advanced" tab, check the box that says "Allow other applications on this computer to communicate with Zotero".

[!IMPORTANT] For access to the /fulltext endpoint on the local API which allows retrieving the full content of items in your library, you'll need to install a Zotero Beta Build (as of 2025-03-30). Once 7.1 is released this will no longer be the case. See https://github.com/zotero/zotero/pull/5004 for more information. If you do not want to do this, use the Web API instead.

To use the Zotero Web API, you'll need to create an API key and find your Library ID (usually your User ID) in your Zotero account settings here: https://www.zotero.org/settings/keys

These are the available configuration options:

  • ZOTERO_LOCAL=true: Use the local Zotero API (default: false, see note below)
  • ZOTERO_API_KEY: Your Zotero API key (not required for the local API)
  • ZOTERO_LIBRARY_ID: Your Zotero library ID (your user ID for user libraries, not required for the local API)
  • ZOTERO_LIBRARY_TYPE: The type of library (user or group, default: user)

uvx with Local Zotero API

To use this with Claude Desktop and a direct python install with uvx, add the following to the mcpServers configuration:

{
  "mcpServers": {
    "zotero": {
      "command": "uvx",
      "args": ["--upgrade", "zotero-mcp"],
      "env": {
        "ZOTERO_LOCAL": "true",
        "ZOTERO_API_KEY": "",
        "ZOTERO_LIBRARY_ID": ""
      }
    }
  }
}

The --upgrade flag is optional and will pull the latest version when new ones are available. If you don't have uvx installed you can use pipx run instead, or clone this repository locally and use the instructions in Development below.

Docker with Zotero Web API

If you want to run this MCP server in a Docker container, you can use the following configuration, inserting your API key and library ID:

{
  "mcpServers": {
    "zotero": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "ZOTERO_API_KEY=PLACEHOLDER",
        "-e", "ZOTERO_LIBRARY_ID=PLACEHOLDER",
        "ghcr.io/kujenga/zotero-mcp:main"
      ],
    }
  }
}

To update to a newer version, run docker pull ghcr.io/kujenga/zotero-mcp:main. It is also possible to use the docker-based installation to talk to the local Zotero API, but you'll need to modify the above command to ensure that there is network connectivity to the Zotero application's local API interface.

Development

Information on making changes and contributing to the project.

  1. Clone this repository
  2. Install dependencies with uv by running: uv sync
  3. Create a .env file in the project root with the environment variables above

Start the MCP Inspector for local development:

npx @modelcontextprotocol/inspector uv run zotero-mcp

To test the local repository against Claude Desktop, run echo $PWD/.venv/bin/zotero-mcp in your shell within this directory, then set the following within your Claude Desktop configuration

{
  "mcpServers": {
    "zotero": {
      "command": "/path/to/zotero-mcp/.venv/bin/zotero-mcp"
      "env": {
        // Whatever configuration is desired.
      }
    }
  }
}

Running Tests

To run the test suite:

uv run pytest

Docker Development

Build the container image with this command:

docker build . -t zotero-mcp:local

To test the container with the MCP inspector, run the following command:

npx @modelcontextprotocol/inspector \
    -e ZOTERO_API_KEY=$ZOTERO_API_KEY \
    -e ZOTERO_LIBRARY_ID=$ZOTERO_LIBRARY_ID \
    docker run --rm -i \
        --env ZOTERO_API_KEY \
        --env ZOTERO_LIBRARY_ID \
        zotero-mcp:local

Relevant Documentation

FAQ

What is the Zotero MCP server?
Zotero is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Zotero?
This profile displays 67 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.667 reviews
  • Amelia Wang· Dec 28, 2024

    I recommend Zotero for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Naina Abbas· Dec 28, 2024

    We wired Zotero into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Chaitanya Patil· Dec 8, 2024

    Useful MCP listing: Zotero is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Amelia Li· Dec 4, 2024

    Zotero is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Piyush G· Nov 27, 2024

    We evaluated Zotero against two servers with overlapping tools; this profile had the clearer scope statement.

  • Naina Singh· Nov 23, 2024

    We wired Zotero into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Neel Park· Nov 19, 2024

    Strong directory entry: Zotero surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Naina Choi· Nov 19, 2024

    Zotero is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Shikha Mishra· Oct 18, 2024

    I recommend Zotero for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Arya White· Oct 14, 2024

    Zotero reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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