A
licenseNot graded
qualityC
maintenanceAn MCP server that acts as an AI knowledge and skills hub, automatically discovering, indexing, and serving skill libraries to any MCP client with full-text search, rich metadata, and hot reload.
MIT
research_mcp
by simonives
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TDQS
A4/5.0
Scored across 27 tools
Disambiguation4/5
Each tool targets a distinct stage of the research workflow (search, retrieval, appraisal, synthesis, design, storage), so most are clearly separable. A few adjacent tools — fetch-url vs extract-from-pdf vs fetch-paper, and appraise-evidence vs appraise-source — could be confused at a glance, but descriptions clarify their boundaries.
Naming Consistency4/5
Tool names are uniformly lowercase and hyphenated, with a dominant verb_noun pattern (search-literature, design-study, check-reporting). A handful of noun-based names (citation-graph, author-profile, people-analytics-preset, workforce-survey-template) break the strict verb-first pattern, but the overall style remains predictable and readable.
Tool Count2/5
With 27 tools, the set exceeds the 25-tool threshold and becomes heavy for an agent to navigate and select from efficiently. While the research domain is broad, several tools could be consolidated (e.g., vault tools, appraisal variants) without losing core functionality.
Completeness4/5
The tool surface covers the full research lifecycle: question scoping, literature search and retrieval, evidence appraisal, synthesis, study design, ethics, reporting, and knowledge management via Zotero and Obsidian. Minor gaps exist — no delete/update for saved Zotero items or vault notes, and no dedicated structured data-extraction tool — but agents can work around these limitations.
Maintenance
ActivityInactive
ResponsivenessNo issues