Zotero MCP
Related Servers
Alternatives to Zotero MCP
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceEnables users to chat with their Zotero research library through AI assistants like Claude and ChatGPT, with support for semantic search, metadata retrieval, annotations, write operations, and citation intelligence.38MIT
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- AlicenseAqualityDmaintenanceEnables AI assistants to search, read, and manage Zotero references locally with customizable research workflows.942 PyPI4MIT
- AlicenseNot gradedqualityBmaintenanceEnables natural language interaction with Zotero libraries, allowing users to search, retrieve, and update papers and metadata via AI assistants like Claude and Gemini.1GPL 2.0
- AlicenseAqualityCmaintenanceEnables read-only search and analysis of your local Zotero library, including full-text PDF retrieval with OCR fallback, annotations, and cross-item comparison for synthesis.13MIT
- AlicenseAqualityCmaintenanceConnects Zotero and Obsidian for an AI-assisted academic reading workflow, enabling paper fetching, structured note creation, highlight syncing, and review management.10MIT
TDQS
Scored across 9 tools
Each tool targets a distinct operation: listing vs searching items, extracting text with or without coordinates, creating single vs batch annotations, adding notes, and listing annotations. Descriptions clearly differentiate them, leaving no ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., 'list_zotero_items', 'create_pdf_annotation'). Even 'batch_annotate' and 'add_child_note' fit the pattern with a verb first. No mixed conventions.
With 9 tools, the server covers the core workflows of Zotero interaction: discovering items, retrieving metadata, extracting PDF text, creating annotations (single/batch), listing annotations, and adding child notes. The count is well-scoped without being too sparse or overwhelming.
The tool set covers the main use cases for reading and annotating Zotero items. However, it lacks tools for updating or deleting annotations, modifying item metadata, or managing collections/tags, which are minor gaps that could cause agents to hit dead ends in some workflows.