Complete Zotero MCP Server for Zotero Web API v3 and Local

An all-in-one Zotero MCP server providing Web API v3 and local API for Claude and other MCP clients, featuring hybrid semantic search.

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Complete Zotero MCP Server

This repository provides a comprehensive MCP server designed to integrate with Zotero, offering robust access to your research data. It supports both Zotero's Web API v3 and a local API, making it a versatile solution for developers working with AI agents and large language models. The server is built to facilitate advanced data retrieval and manipulation, enabling sophisticated applications that leverage your Zotero library.

What it Does

The Complete Zotero MCP Server acts as a bridge between your Zotero data and AI clients, such as Claude. It exposes Zotero's extensive bibliographic information through a standardized MCP (Machine Communication Protocol) interface. This allows AI agents to query, retrieve, and potentially modify items within your Zotero library programmatically. The inclusion of hybrid semantic search capabilities enhances the relevance and depth of information accessible to these agents.

Key Features

Zotero Web API v3 Support: Seamless integration with the latest Zotero API for remote data access.
Local API: Provides direct access to Zotero data on your local machine, reducing latency and dependency on external services.
Hybrid Semantic Search: Combines traditional keyword search with advanced semantic understanding for more accurate results.
MCP Protocol: Adheres to the Machine Communication Protocol for standardized AI agent interaction.
Developer-Focused: Designed for developers needing programmatic access to Zotero for AI projects.

Who it's For

This tool is specifically for AI builders , researchers , and developers who utilize Zotero as their primary reference management system. If you are developing AI agents that need to interact with academic literature, research papers, or any data stored in Zotero, this MCP server will provide the necessary infrastructure. It's ideal for projects involving literature review automation, knowledge graph construction from research, or building intelligent assistants for academic workflows.