xknow-mcp
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- AlicenseNot gradedqualityBmaintenanceEnables AI agents to perform local-first web search, fetch, crawl, extract, cache, research, and autonomous information gathering through MCP, with no API keys or cloud dependencies.3,236 npmAGPL 3.0
- FlicenseNot gradedqualityAmaintenanceEnables MCP-compatible AI agents to search, ask, and retrieve section-level cited answers from a local hybrid index over scattered notes, documents, and chat logs.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents and MCP-compatible hosts to search, ask, and retrieve section-level citations from scattered local notes, docs, PDFs, Word files, web pages, org files, and chat logs using hybrid vector and BM25 retrieval.-
TDQS
Scored across 5 tools
Each tool targets a distinct operation: search, read, explore graph, list, and cite. No overlap in purpose or output, making selection straightforward.
Mostly consistent verb_noun patterns (search_knowledge, get_page, explore_concept, list_topics), but 'cite' deviates as a bare verb without an object. Minor inconsistency.
Five tools perfectly cover the core workflows of a knowledge retrieval server: discover, search, read, explore connections, and cite. Well-scoped with no extraneous tools.
Covers all essential operations for a read-only knowledge base. Missing tools for editing or adding notes, but the server appears curated and source-backed, so writes may be intentionally out of scope.