MCP Zotero

Overview

The MCP Zotero server bridges the gap between Claude and your personal research library. By exposing a set of intuitive tools that mirror Zotero’s core API endpoints, it lets an AI assistant read, search, and manipulate bibliographic data without the developer writing custom integration code. For researchers, writers, or anyone who relies on Zotero for reference management, this server eliminates the friction of manually exporting citations or building bespoke connectors.

What Problem Does It Solve?

Managing a large library in Zotero can become cumbersome when you need to retrieve specific items, filter by collection, or pull metadata for downstream tasks. Traditionally, developers would need to write HTTP clients, handle authentication tokens, and parse JSON responses for each operation. MCP Zotero consolidates these responsibilities into a single, well‑defined server that Claude can call through the Model Context Protocol. This reduces boilerplate, ensures consistent error handling, and keeps sensitive API keys out of the assistant’s prompt.

Key Features & Capabilities

• Collection Management – lists every collection in the library, allowing the assistant to present a navigable hierarchy or suggest relevant folders for new entries.
• Item Retrieval – and fetch the raw data or a detailed view of any paper, including authors, publication date, and abstract.
• Full‑Text Search – performs keyword queries across all items, returning ranked results that can be used for literature reviews or topic exploration.
• Recent Additions – surfaces the newest entries, enabling timely reminders or updates on freshly imported research.
• Secure Authentication – The server requires a Zotero API key and user ID, ensuring that only authorized requests reach the library. These credentials are passed via environment variables, keeping them out of the assistant’s memory.

Real‑World Use Cases

• Academic Writing – A researcher can ask Claude to pull the citation details of a paper by title, and the assistant returns formatted references or BibTeX entries automatically.
• Literature Review Automation – By querying , Claude can surface all papers on a given topic, summarize them, and suggest new keywords for deeper exploration.
• Reference Management – When adding a new article, the assistant can invoke to confirm that the item was imported correctly and then organize it into an appropriate collection.
• Collaboration – Teams using shared Zotero libraries can let Claude fetch group collections and share insights across members without manual data sharing.

Integration with AI Workflows

The server is designed to plug directly into Claude Desktop’s MCP configuration. Once the environment variables are set, developers add a single command entry to their settings. From there, Claude can issue any of the exposed tool calls with a simple JSON payload. The responses are returned in a structured format, ready for the assistant to incorporate into its replies or further processing. This tight integration means that developers can focus on higher‑level conversational logic while the MCP server handles all the data retrieval intricacies.

Standout Advantages

• Zero‑Code Connector – No need to write custom API wrappers; the MCP server handles authentication, rate limiting, and data normalization.
• Security‑First Design – Credentials are never exposed to the assistant’s prompt, reducing the risk of accidental leaks.
• Extensibility – The tool list mirrors Zotero’s API, so adding new capabilities is straightforward and keeps the interface future‑proof.
• Community Trust – Published on NPM with a clear version badge and hosted by Smithery, the server benefits from community maintenance and transparency.

In sum, MCP Zotero transforms a static reference library into an interactive knowledge base that Claude can query on demand. It streamlines research workflows, enhances productivity, and exemplifies how Model Context Protocol servers can turn specialized services into conversational assets.