# Zotero

> Use this tool when you need to integrate your Zotero reference library with AI-assisted workflows, automating tasks such as literature review, citation management, and content summarization. It provides a bridge between AI agents and scholarly research data, allowing for searching, metadata retrieval, and full-text access. By leveraging this tool, researchers and knowledge workers can streamline their workflows without directly interacting with the Zotero API.

Canonical page: https://skillsregistry.net/skills/kujenga-zotero  
JSON: https://api.skillsregistry.net/v1/skills/kujenga-zotero

## Description

This MCP server, developed by an unknown author, provides integration with the Zotero reference management system. Built with Python and leveraging the pyzotero library, it offers tools for searching Zotero libraries, retrieving item metadata, and accessing full-text content. The implementation focuses on providing a bridge between AI agents and scholarly research data, with features like formatted metadata output and attachment handling. It's particularly useful for researchers, students, and knowledge workers looking to incorporate their Zotero libraries into AI-assisted workflows, enabling use cases such as literature review automation, citation management, and content summarization without directly interacting with the Zotero API.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kujenga-zotero)
- **Repository:** <https://github.com/kujenga/zotero-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kujenga-zotero"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kujenga-zotero` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kujenga-zotero/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt