Semantic Cache MCP
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- AlicenseNot gradedqualityDmaintenanceProvides file caching and diff tracking for AI coding agents, reducing token usage by returning changes or confirming no changes instead of full file contents on repeated reads.35 npm220MIT
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- AlicenseAqualityCmaintenanceProvides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.558 npm63TypeScriptMIT
TDQS
Scored across 14 tools
Tools are largely distinct: read vs batch_read (one vs many), edit vs batch_edit (one vs many), edit vs edit_preview (apply vs probe), search (BM25 concept) vs grep (exact/regex), read (text) vs read_image (images). The main soft spot is the discovery cluster (warm, glob, search, grep), which all deal with cached files, but the descriptions draw clear boundaries between indexing and searching.
Names are consistently snake_case and mostly verb-led (read, write, edit, delete, search, warm, grep, clear), with predictable batch_ and edit_preview qualifiers. Minor deviations are the noun-style names stats and glob, which break the verb pattern but remain readable and unambiguous.
14 tools sit comfortably in the well-scoped 3-15 range, and each earns its place by covering a distinct slice of file I/O plus cache management. No redundant or filler tools are present.
Core lifecycle is covered: create (write), read (read/batch_read), update (edit/batch_edit), delete, plus discovery (glob/grep/search/warm) and diagnostics (stats/clear). Gaps like directory creation, move/rename, and symlink operations are minor and workable, but agents needing those will hit dead ends.