everything-semantic-mcp
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- AlicenseAqualityAmaintenanceEnables AI assistants to search local files and folders via the Everything search engine, with support for advanced queries, file metadata, text previews, and service status.6MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to search local files on Windows using the Everything search engine, supporting basic and complex file searches with filters like date, size, media type, and document type.12 PyPI4MIT
- AlicenseAqualityCmaintenanceEnables AI clients to search and count indexed files and folders through Everything's HTTP JSON API, retrieve real-time file metadata, reveal items in Explorer, and automatically launch Everything with UAC when needed.4MIT
- AlicenseAqualityCmaintenanceEnables AI agents on Windows to perform millisecond-level file searches across entire drives via voidtools Everything, with path scoping, noise filtering, and token-efficient output.2MIT
- AlicenseBqualityDmaintenanceIntegrates voidtools Everything search engine with AI assistants to provide lightning-fast file search, GitHub integration, intent-based code research, and spec-driven development tools for Windows.5547 npm2MIT
- AlicenseNot gradedqualityBmaintenanceExposes the local voidtools Everything index over MCP stdio on Windows, letting AI agents search, filter, aggregate, detect duplicates and grep file contents across millions of index entries in milliseconds instead of recursively scanning disks. It provides 13 tools and 3 resources, running loopback-only and read-only by default.MIT
TDQS
Scored across 9 tools
Each tool has a recognizable purpose: literal search vs semantic search is clearly split, and count/recent/largest/health/maintain/reindex/status all target distinct operations. The only mild overlap is that everything_recent and everything_largest are effectively presets of everything_search with a sort argument, but the descriptions frame them distinctly enough that misselection is unlikely.
Every tool uses the same everything_ prefix followed by a clear action descriptor (search, count, recent, largest, health, maintain, and the semantic_ family). The verb_noun-ish pattern is consistent across the whole set, including the namespaced semantic group.
Nine tools is well within the ideal 3-15 range for a focused file-search server. Each earns its place: two search modes, three aggregation helpers, two index-health tools, and two semantic-index lifecycle tools.
The surface covers literal and semantic discovery, aggregation (count/recent/largest), and index health/maintenance/reindex lifecycle well, so core workflows have no dead ends. Minor gaps remain, such as opening/revealing the file found or exporting results, which agents would have to work around.