프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

Rangefind

제작자: xjodoin버전 0.3.2i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.xjodoin/rangefind

설치

개요

제작자가 쓴 설명(영어 원문)

Search rangefind static indexes: full-text, geo, autocomplete, facets - no server, just files.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 검색 및 AI 기억

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "rangefind": {
      "command": "npx",
      "args": [
        "-y",
        "rangefind-mcp"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add rangefind -- npx -y rangefind-mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "rangefind": {
      "command": "npx",
      "args": [
        "-y",
        "rangefind-mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "rangefind": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "rangefind-mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 xjodoin 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 7256개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7256개 중 22%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7256개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Rangefind, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.2)은 4개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT오늘 업데이트
설치

Codebase Memory

제작자: DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

내 컴퓨터에서 실행★ 48,148MIT20일 전 업데이트
설치

Exa

제작자: exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

클라우드에서 실행★ 5,213MIT지난달 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

Rangefind

Rangefind is a static search engine for large sites that cannot or should not run a search server.

It builds a sparse inverted index into static files, then lets the browser query that index with HTTP Range requests. The core idea is simple: keep the logical search shards small, but pack them into a small number of static files so deploys and cold starts stay practical.

This repository is the standalone extraction of a production prototype built for a large thesis corpus.

What Is Implemented

The list below is the compact overview. The [complete feature guide](docs/features.md) explains every supported search lane, build mode, runtime, integration, feature combination, fallback, and deliberate boundary with runnable examples.

  • JSONL document input.
  • Static-site crawler: rangefind build ./dist indexes built HTML directly, with data-rangefind-* attributes for body scoping, metadata, facets, and sorts.
  • Schema-driven weighted fields.
  • BM25F-style field scoring.
  • Phrase signals for title/heading fields.
  • Adaptive posting segments.
  • Independently compressed posting segments packed into terms/packs/*.bin.gz.
  • Single ESM browser runtime bundle at dist/runtime.browser.js.
  • Node runtime (rangefind/node) for MCP servers, CLIs, and SSR: same query engine over local index directories (positional file reads) or remote HTTP(S) indexes, with browser-equivalent caching — immutable content-addressed objects cached on disk and in a memory LRU, manifests revalidated with ETags.
  • Mobile runtime (rangefind/mobile) for React Native/Hermes and other embedded JS hosts: fully offline search over a bundled or downloaded index via positional file reads, or remote HTTP(S) indexes with memory + persistent caching — see docs/mobile.md (covers WebView, Flutter, and native apps too).
  • Lazy paged binary range directories at terms/directory-root. .bin.gz and terms/directory-pages/*.bin.gz.
  • ZFS-inspired object pointers with SHA-256 verification before decompression.
  • Content-addressed immutable pack and directory filenames for CDN caching.
  • Exact compressed-object deduplication during index construction.
  • Locality-ordered doc packs with a tiny doc-id ordinal table and dense pointer records for low-transfer result fetching.
  • Dense binary doc-page payload packs for browse, filter, and sort result pages where original document ids are clustered.
  • Range-packed result payloads with capped display fields.
  • Range-addressable posting-block sidecar for high-df terms.
  • Optional authority sidecar for exact title/entity/alias rescue without changing the main inverted index; a single title authority also supplies bounded prefix autocomplete without a second large build structure.
  • Range-packed binary facet dictionaries for high-cardinality metadata.
  • File-backed build pipeline with immutable posting segments, selected-term spools, raw/compressed document spools, heap-based segment merge, and sampled build telemetry.
  • Minimal runtime manifest with lazy full-manifest and telemetry sidecars.
  • Browser runtime with adaptive HTTP Range coalescing and bounded overfetch.
  • Main-index typo correction that uses bounded vocabulary shard probes and executes only the strongest corrected searches when first-page results are empty or weak.
  • Multi-value keyword facets with lazy dictionary loading.
  • Range-addressed typed numeric, date, and boolean doc-values for filters and sorting.
  • Lazy binary sorted doc-value trees for range-pruned top-k sort and doc-order early-stop browsing.
  • Lucene-style geo point fields with a range-addressed static KD tree: bounding-box and radius filters, exact nearest-neighbor distance sort with early-stop proofs (with or without a text query), text-plus-geo filtering, per-cell filter summaries, and distance boosts.
  • Optional compact geo result capsules and multi-resolution facet-to-cell indexes for one-range map results and category-aware spatial routing, plus a wildcard occupancy lane for arbitrary names and brands.
  • Generic route-corridor search over encoded polylines, coordinate arrays, or GeoJSON: exact point-to-route filtering, multi-resolution corridor cells, progress/direction/viewport ranking, and a rejoin point for every result.
  • Static routing and itinerary planning (rangefind/route): a CRP/MLD route graph built from OSM road networks into range-addressed cell and overlay objects — point-to-point driving routes with geometry and named steps, travel-time matrices, and multi-stop itinerary optimization, all exact versus a full-graph Dijkstra and served from static files with a bounded fetch set per query; sharded builds share one top overlay and route identically to monolithic ones — see docs/route-graph.md.
  • Search-as-you-type autocomplete inside the range-addressed authority index: diacritic-folded prefix and mid-label token matching, popularity or custom weights, exact best-first top-k with per-shard weight proofs, and precomputed hot lists so a first keystroke costs one small fetch—without a second suggestion pack family or a corpus-sized heap map.
  • Hybrid semantic search from a range-addressed IVF vector index: int8 quantized embeddings, coarse-dimension candidate pages plus a fixed-width full-dimension refine store, cosine top-k, and reciprocal-rank fusion with the text lane — no server, no vector database.
  • Analyzer-consistent snippets and highlight ranges on search results.
  • Multilingual analysis (analysis config): per-document language detection or an explicit language field, per-language light stemmers and stopwords for 20+ languages, script-aware Unicode folding (Latin, Greek, Cyrillic, Arabic, Hebrew, Devanagari), dictionary-free CJK bigram tokenization that is deterministic across Node and every browser, cross-language query expansion with index-evidence base-plan selection, and the whole profile frozen into the manifest so query analysis always matches the index.
  • Incremental publishing: rangefind build --update adds small delta generations over an existing index — unchanged pack bytes keep their content-addressed names (and CDN cache entries), replaced documents tombstone their old version, and the runtime merges every lane (text, sorted browse, geo, vector, hybrid, suggest, facets) across generations with scores that stay exactly comparable. rangefind build --compact folds generations back into a single index when they pile up.
  • Per-query facet counts with exact-or-flagged semantics: dictionary-backed global counts, exact counts over budgeted match sets, and bounded chunk-sampled estimates for very large result sets.
  • OpenStreetMap place and address fixture with canonical zero-posting address lookup, compact addr:interpolation ranges, structured forward and reverse geocoding, bounded multi-provider civic/postal augmentation (including the Québec RQA adapter), reusable rangefind/osm and rangefind/osm/node integration APIs, and exhaustive geo oracles.
  • OSM typed and natural-language constraints for accessibility, services, payment, seating, reservations, fees, and open-now; conservative client-side opening_hours evaluation; route-aware place search; compact place details; and simplified encoded area geometry for real polygon/line map rendering.
  • Geographic index sharding for planet-scale corpora: independently built and updated per-region shards sharing one frozen scoring-stats artifact (scoringStats config + rangefind/scoring-stats), a tiny sharded root manifest (rangefind/shards), lazy shard engines with bbox geo routing and expanding nearest-first search, and merged lanes whose rankings match a monolithic build of the same corpus exactly — see docs/sharded-osm.md.
  • Link-graph authority (linkRank): the static-site crawler resolves internal links into a document graph and folds a build-time PageRank prior into a sortable numeric doc-value. Well-linked pages win near-ties in ranking (an opt-out multiplicative boost, score *= 1 + boost*linkRank, applied as a bounded window rerank with no change to the scoring hot loop), you can sort by authority, and there is zero query-time graph traversal. Any corpus that knows its own edges can opt in with the turnkey examples/link-graph-enrich.mjs enricher (or the exported rangefind/link-graph helper); see docs/link-graph.md.
  • Tiny runnable example.

Why This Exists

Most browser search libraries assume the browser downloads a whole index, or they optimize for smaller sites. Rangefind is for the case where you want:

  • no backend service,
  • no hosted search provider,
  • static hosting compatibility,
  • measurable retrieval quality,
  • low request count despite many logical shards,
  • and an index format designed around top-k retrieval.

Quick Start

Demos: https://rangefind.dev/ — an OpenStreetMap map search backed by the rolling public sharded index (autocomplete, viewport geo queries, and nearest-neighbor) and the minimal example, both served as pure static files.

The already-generated planet-scale OSM index is free to query directly from browsers or Node—no account or API key required:

import { createSearch } from "rangefind";

const engine = await createSearch({ baseUrl: "https://osm.rangefind.dev/" });

See its live coverage and freshness at https://osm.rangefind.dev/. It is a best-effort public service; self-host the index when you need guaranteed capacity, version pinning, custom fields, or an operational SLA. OSM result UIs must display © OpenStreetMap contributors.

npm install

npm run build:example npm run test:smoke npm run serve:example

Open http://localhost:5178/.

Documentation

Start with the guide that matches the job:

GuideUse it for
[Feature guide](docs/features.md)Complete capability catalog, examples, supported combinations, compatibility, and boundaries.
[Reference](docs/reference.md)Configuration properties, builder/runtime APIs, tuning knobs, UI component, and deployment requirements.
[Architecture](docs/architecture.md)Static file layout, range directories, posting retrieval, geo, authority, and vector internals.
[Autocomplete guide](docs/autocomplete.md)Search-as-you-type patterns, measured per-keystroke costs, hydrated previews, instant selection, and the anti-patterns.
[OSM example](examples/osm-geo/README.md)Map search, autocomplete, geocoding, constraints, route corridors, geometry, extraction, and RQA.
[Replace Google Maps APIs](https://rangefind.dev/google-maps-api-alternative/)Free public OSM index, migration adapter, API mapping, complete use cases, production checklist, attribution, and parity boundaries.
[Node](docs/node-runtime.md) / [mobile](docs/mobile.md)Local, remote, cached, embedded, and offline runtimes.
[Sharded OSM](docs/sharded-osm.md)Planet-scale regional builds, root routing, and exact score comparability.
[Route graph](docs/route-graph.md)Static routing, travel-time matrices, and itinerary planning over range-addressed road-network cells and overlays.
[Production maps benchmark](docs/osm-maps-benchmark.md)Google Maps-style workload coverage, quality assertions, and phone budgets.

Crawl A Static Site

If you already have a built static site (from any generator), point Rangefind at the output directory and it indexes the HTML directly — no JSONL to author:

npx rangefind build ./dist

This crawls every .html/.htm file under ./dist, extracts the title, headings, and main body text, and writes the index to ./dist/rangefind (change it with --output). Result URLs default to site-root paths (--base-url sets a prefix or origin, e.g. --base-url https://example.com/). Deploy the site and

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

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