Scholar MCP Server
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TDQS
Scored across 7 tools
Most tools have distinct purposes with clear boundaries: paper_ai_analyze focuses on AI analysis, paper_citation_graph on citation visualization, paper_recommend on workspace-based recommendations, and paper_health on service monitoring. However, paper_download and paper_batch_download overlap significantly in functionality, with the batch version essentially being a multi-DOI extension of the single download tool, which could cause confusion about when to use each.
All tools follow a consistent 'paper_' prefix with descriptive snake_case naming that clearly indicates their function. The pattern is uniform across all seven tools, making them predictable and easy to understand at a glance. No mixing of naming conventions or inconsistent verb styles is present.
With 7 tools, this server is well-scoped for academic paper management and analysis. Each tool serves a distinct role in the workflow: searching, downloading, analyzing, visualizing citations, checking service health, and generating recommendations. The count is appropriate for the domain without being overwhelming or insufficient.
The toolset covers most core academic paper workflows comprehensively: search, download (single and batch), analysis, citation visualization, and recommendation. A minor gap exists in update/management operations (e.g., organizing downloaded papers, managing collections, or tracking reading status), but agents can work effectively with the provided tools for typical research tasks.