Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Search rangefind static indexes: full-text, geo, autocomplete, facets - no server, just files.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"rangefind": {
"command": "npx",
"args": [
"-y",
"rangefind-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add rangefind -- npx -y rangefind-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"rangefind": {
"command": "npx",
"args": [
"-y",
"rangefind-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"rangefind": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"rangefind-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub xjodoin, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.3.2) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.
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.
rangefind build ./dist indexes built HTML directly, with data-rangefind-* attributes for body scoping, metadata, facets, and sorts.terms/packs/*.bin.gz.dist/runtime.browser.js.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.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).terms/directory-root. .bin.gz and terms/directory-pages/*.bin.gz.Range coalescing and bounded overfetch.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.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.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.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.opening_hours evaluation; route-aware place search; compact place details; and simplified encoded area geometry for real polygon/line map rendering.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.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.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:
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/.
Start with the guide that matches the job:
| Guide | Use 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. |
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
Solo se muestra el principio; lee el resto en el repo