meilisearch

name	meilisearch
description	Meilisearch open-source search engine with full-text, semantic, and hybrid search, filtering, faceting, and typo tolerance. Use when integrating Meilisearch, building search UIs, configuring indexes, embedders, ranking, filters, tenant tokens, or self-hosting.
metadata	{"source":"Generated from https://www.meilisearch.com/docs/llms.txt"}

Meilisearch is an open-source, RESTful search engine optimized for fast, relevant, typo-tolerant search. It supports full-text, semantic, and hybrid (AI-powered) search, plus filtering, sorting, faceting, geosearch, and multi-tenancy. Available as Meilisearch Cloud or self-hosted; default port is 7700.

Core concepts

• Instance: a running Meilisearch server, secured by a master key (self-hosted) and scoped API keys.
• Index: a collection of documents with its own settings, identified by a uid (e.g. movies). Similar to a SQL table.
• Document: a JSON object with fields. Each document must have a unique primary key (e.g. id).
• Task: writes (add documents, update settings) are asynchronous and return a taskUid. Poll the task or use waitForTask to confirm completion.
• Settings: per-index configuration controlling searchable/filterable/sortable attributes, ranking rules, synonyms, typo tolerance, embedders, etc.

Quick start (JavaScript SDK)

Install the official client and search in a few lines. Writes are async, so wait for the task before searching.

npm install meilisearch

import { Meilisearch } from 'meilisearch'

const client = new Meilisearch({
  host: process.env.MEILISEARCH_URL, // e.g. http://localhost:7700
  apiKey: process.env.MEILISEARCH_KEY,
})

const task = await client.index('movies').addDocuments([
  { id: 1, title: 'The Matrix', genres: ['Action', 'Sci-Fi'], year: 1999 },
  { id: 2, title: 'Inception', genres: ['Action', 'Thriller'], year: 2010 },
])
await client.waitForTask(task.taskUid)

const results = await client.index('movies').search('matrix')

To filter, first declare filterable attributes, then pass a filter:

await client.index('movies').updateFilterableAttributes(['genres', 'year'])
const { hits } = await client.index('movies').search('', {
  filter: 'genres = "Sci-Fi" AND year > 2000',
})

When to use which reference

Topic	Description	Reference
Getting started	Install (Docker/cURL/Cloud), connect, official SDKs, framework guides	getting-started
Search	/search parameters, pagination, highlighting/cropping, multi-search, federation	search
Filtering, sorting, faceting	Filter expression syntax, operators, facets, geosearch	filtering-sorting-faceting
Indexing	Documents, primary key, async tasks, batches, large imports	indexing
Relevancy	Ranking rules, custom ranking, typo tolerance, synonyms, stop words	relevancy
AI-powered search	Embedders, hybrid/semantic search, similar documents, conversational search	ai-search
Index settings & API	Full REST endpoint map and settings reference	api-reference
Security	API keys, tenant tokens, multitenancy	security
Self-hosting	Configuration, deployment, backups (dumps/snapshots), sharding	self-hosting

Key rules to remember

• All write operations are asynchronous. Always confirm via task status before relying on the result.
• An attribute must be in filterableAttributes before you can filter/facet on it, and in sortableAttributes before you can sort on it.
• PATCH /indexes/{uid}/settings (and updateSettings) merges only the fields you send; sending null resets a setting to default.
• Updating an index that does not exist via document or settings routes creates it automatically.
• Prefer the POST /search route over GET for auth caching and performance.
• Never expose the master key or admin API key to clients; use a search-only key or tenant token in the browser.