everything-semantic-mcp
Use this MCP server to search, inspect, and maintain indexed files/folders by name, metadata, and meaning.
Search file/folder names and paths with Everything query syntax, including filters, sorting, regex, case/word matching, details, and pagination.
Count matches for up to 20 queries at once.
Find recently modified files or largest files, optionally scoped by path, extension, or minimum size.
Run fully local multilingual semantic search over folder/document names.
Build/reindex the semantic index and check its status.
Diagnose Everything index health/configuration and run maintenance actions such as saving the DB, rescanning folders, or rebuilding.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@everything-semantic-mcp Find the new employee onboarding guide by meaning"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
findex
파일 이름을 몰라도 찾는 검색 — 사람은 검색 창으로, AI 에이전트는 MCP로. Windows · macOS · Linux 실행 파일 하나. 설치·Python 불필요.
한국어 · English
이런 걸 찾습니다
이렇게 검색하면 | 이름 검색만으로는 | findex |
| 0건 (예: 실제 폴더명이 "신입사원 온보딩 가이드"일 때) | 상위로 찾음 |
| 0건 ("위치"라는 단어가 이름에 없음) | "2026 Q3 매출 보고서" 폴더 상위 |
| 정상 | 그대로 정확 검색 |
이름 검색: Everything 문법(
ext:,path:,dm:,size:,folder:,!,|,*).단어 하나가 안 맞아도: 모든 단어가 들어간 항목이 없으면, 가장 많은 단어가 맞는 순으로 보여줍니다(BM25 보조).
뜻으로 찾기: 폴더·문서 이름을 다국어 임베딩으로 색인. 한국어·영어 섞어도 됩니다. 전부 내 PC 안에서.
Related MCP server: everything-search-mcp
시작하기 (1분)
Releases 에서 내 OS 파일을 받습니다.
OS
파일
Windows 10/11
findex-windows-x64.exemacOS Apple Silicon (M1~)
findex-macos-arm64(Intel Mac: 소스로 실행, 아래 참고)Linux x64
findex-linux-x64실행 — 더블클릭하면 브라우저에 검색 창이 열립니다.
Windows SmartScreen이 막으면 "추가 정보 → 실행" (서명 인증서 없는 오픈소스 빌드).
macOS: 터미널에서
xattr -d com.apple.quarantine ~/Downloads/findex-macos-*; chmod +x ~/Downloads/findex-macos-*후 실행.Linux:
chmod +x findex-linux-x64 && ./findex-linux-x64
처음 한 번 검색 창 위쪽의 "의미 색인 만들기" 를 누릅니다(모델 약 120MB 자동 다운로드, 수 분).
어떤 색인을 쓰나요?
Windows + Everything 실행 중 → Everything의 색인을 그대로 사용(수백만 개도 즉시).
그 외(macOS·Linux·Everything 없는 Windows) → findex가 자체 색인을 만듭니다. 첫 실행 때 홈 폴더(Windows는 고정 드라이브 전체)를 스캔합니다.
범위 바꾸기:
findex roots add /Volumes/NAS,findex roots remove ~/Downloads, 다시 스캔:findex scan
AI 에이전트에 연결 (MCP)
실행 파일 경로를 command로, 인자 mcp를 넣으면 됩니다.
Claude Code
claude mcp add findex -- /경로/findex mcpClaude Desktop (claude_desktop_config.json)
{ "mcpServers": { "findex": { "command": "C:\\Tools\\findex-windows-x64.exe", "args": ["mcp"] } } }Codex CLI / Cursor / gjc 등: 같은 command + args: ["mcp"].
에이전트가 쓰는 도구:
도구 | 용도 |
| 자연어 요청 한 번에 — 이름 매칭 + 의미 검색 융합 |
| 정확한 이름 검색·필터·정렬 (0건이면 가장 많이 맞는 순으로 자동 완화) |
| 건수 비교 / 최근 수정 / 큰 파일 |
| 의미만으로 검색 / 의미 색인 생성 |
| 상태 / 자체 색인 재스캔 |
| Everything 설정 자가 진단 / DB 저장·재스캔 (Windows + Everything) |
명령줄
findex 검색 창 열기 (기본)
findex mcp MCP 서버 (stdio)
findex scan 자체 이름 색인 새로고침
findex reindex 의미 색인 만들기
findex roots [add|remove DIR] 자체 색인 범위
findex status | health측정값
Windows 11 · i7-1255U · Everything 1.4.1.1032 x64 · 색인 6,126,653 항목(로컬 + 네트워크 폴더):
항목 | 값 |
의미 색인 | 1,177,343개 이름, 생성 264초 |
의미 검색 1회 (중앙값) | 45~58 ms |
| 약 440 ms |
2단계 재정렬 recall@20 | 0.98 (전수 256차원 대비) |
시작 직후 첫 의미 검색 | 모델 로딩 약 20초 — 검색 창은 이름 결과를 먼저 보여주고 의미 결과는 준비되면 합류 |
실제 사내 경로 78만 개로 평가한 검색 방식 비교(한 단어가 이름에 없는 질의 200개): 엄격한 이름 검색은 89%가 0건, 단어 완화 + 순위(findex)는 53%가 상위 10위 안에 정답. 주제 질의 20개는 이름+의미 융합이 상위 10위 적중 0.90~0.95.
개인정보
파일 내용은 읽지 않고 이름·경로·크기·날짜만 색인합니다.
모든 처리는 내 PC 안에서. 외부 전송은 최초 모델 다운로드(Hugging Face)뿐입니다.
색인 위치: Windows
%LOCALAPPDATA%\findex, macOS~/Library/Application Support/findex, Linux~/.local/share/findex. 경로가 평문으로 저장되니 공유 PC라면 권한을 확인하세요.검색 창은
127.0.0.1에만 열립니다(외부 접속 불가).
소스로 실행 / 개발
git clone https://github.com/yazzang-homelab/everything-semantic-mcp
cd everything-semantic-mcp
pip install -e ".[dev]"
findex # 또는 python -m everything_semantic_mcp
pytest실행 파일 빌드: cd packaging && pyinstaller findex.spec (각 OS에서). 태그(v*)를 올리면 GitHub Actions가 4개 OS용으로 빌드·테스트·릴리스합니다.
관련 프로젝트
elis132/everything-mcp(es.exe 기반, 느린 쿼리 보호), mamertofabian/mcp-everything-search(SDK DLL, macOS/Linux 지원). findex는 독립적으로 작성했고 의미 검색 + 단어 완화 검색 + 사람용 검색 창 + 단일 실행 파일에 집중합니다.
라이선스
MIT. voidtools Everything의 비공식 연동이며, Everything은 voidtools의 상표입니다.
Available Tools
9 toolseverything_countA
Count matches for up to 20 queries in one call (no rows returned), e.g. compare 'ext:pdf' vs 'ext:docx' under a folder, or check whether a file exists anywhere.
Inputs: queries (required), match_path.
everything_healthA
Index health and configuration self-check: version, build (x86/x64), database state, indexed volumes and folders, database age, and settings that cause slow indexing, RAM bloat or freezes (a drive indexed twice, change monitoring on network folders, foreground rescans, rescans at every startup, an index never saved, the 32-bit build). Each issue has a fix.
Inputs: no named parameters.
everything_largestA
Largest files (optionally under a folder or share), for disk-usage triage. min_size: '100mb', '1gb'.
Inputs: limit, min_size, path_filter.
everything_maintainA
Index maintenance. save_db: persist the in-memory index (fast restart). rescan_folders: refresh folder indexes (network shares) now. rebuild: full re-index (slow; only if results look stale).
Inputs: action (required).
everything_recentA
Most recently modified files, newest first.
path_filter: restrict to a folder or share. extensions: ';'-separated, e.g. 'xlsx;csv'. within: today | yesterday | last7days | last30days | thisweek | thismonth | 2026-10.
Inputs: limit, within, extensions, path_filter.
everything_searchB
Search file and folder names across every drive and network folder Everything indexes.
query: Everything syntax, e.g. 'ext:xlsx budget dm:last30days', 'path:"D:\Projects" *.pptx',
'folder: invoices', '"exact name.txt"'. An empty query matches everything (use with filters).
limit: 1-500 rows; total in the response tells you whether to narrow the query.
sort: name (always instant) | date_modified_desc for "latest" | size_desc for "largest".
details: include size (bytes) and modification date; false returns bare paths (folders end with '').
match_path: match terms against the full path instead of just the name.
Inputs: query (required), sort, limit, regex, +5 more.
everything_semantic_reindexA
(Re)build the local semantic index from the live Everything database. Runs in the background unless wait=true (~3-7 min per million names on a laptop CPU); poll everything_semantic_status.
Inputs: wait.
everything_semantic_searchA
Meaning-based search over folder names and document file names (multilingual, fully local). Use when the user describes WHAT they want rather than a literal name: 'last quarter's sales deck', '세금 계산서 모음', 'onboarding material'. Scores: >0.6 strong, 0.4-0.6 related. path_prefix restricts to a drive or share. Folders end with ''; list their contents with everything_search('parent:""').
Inputs: query (required), kind, limit, path_prefix.
everything_semantic_statusC
Semantic index metadata (count, built_at, model), its location, and any running or failed build.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
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.
Maintenance
Related MCP Connectors
Universal persistent memory and knowledge retrieval layer for AI agents and LLMs.
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
Read and search folders on your own computer with explicit consent. Files are never uploaded.
A search engine that learns from your grades. Store text, records, images or embeddings.
Related MCP Servers
- 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.5157 npm2MIT
- 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.15 PyPI4MIT
- AlicenseAqualityBmaintenanceEnables 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.6157 npmMIT
- 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