[ { "id": "meilisearch-docs-1", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/getting_started/overview", "excerpt": "It stores your documents and embeddings, then exposes them through fast full-text search, semantic search, and conversational interfaces, all from a single API.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-2", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/getting_started/first_project.md", "excerpt": "creating a project and an index, adding documents to it, and performing your first search with the default web interface", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-3", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/full_text_search/relevancy/typo_tolerance_settings.md", "excerpt": "Typo tolerance helps users find relevant results even when their search queries contain spelling mistakes or typos, for example, typing `phnoe` instead of `phone`.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-4", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/full_text_search/relevancy/ranking_rules.md", "excerpt": "Meilisearch contains seven built-in ranking rules in the following order: [\"words\", \"typo\", \"proximity\", \"attributeRank\", \"sort\", \"wordPosition\", \"exactness\"]", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-5", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/full_text_search/relevancy/synonyms.md", "excerpt": "If multiple words have an equivalent meaning in your dataset, you can create a list of synonyms. This will make your search results more relevant.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-6", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/filtering_sorting_faceting/overview.md", "excerpt": "E-commerce faceted navigation: Let shoppers narrow products by brand, color, size, and price range while displaying counts for each option.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-7", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/filtering_sorting_faceting/how_to/facet_search.md", "excerpt": "It is typically used to power auto-complete and type-ahead interfaces on top of filter menus, especially when a facet has too many distinct values to display at once", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-8", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/hybrid_search/overview.md", "excerpt": "When you configure an embedder, Meilisearch automatically generates vector embeddings for every document in your index. You don't need to compute or manage embeddings yourself.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-9", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/analytics/overview.md", "excerpt": "Track search queries, click events, and conversions to measure search quality and identify opportunities for improvement.", "fetchedAt": "2026-09-06T21:57:56.810Z" }, { "id": "meilisearch-docs-10", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/security/overview.md", "excerpt": "Tenant tokens are short-lived, scoped credentials generated from an API key. 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This gives users the best of both worlds", "fetchedAt": "2026-09-06T22:03:27.424Z" }, { "id": "meilisearch-docs-34", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/filtering_sorting_faceting/overview.md", "excerpt": "Facets are filters that also return distribution data. Use them together to build interactive, ecommerce-style navigation.", "fetchedAt": "2026-09-06T22:03:27.424Z" }, { "id": "meilisearch-docs-35", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/security/overview.md", "excerpt": "Tenant tokens... embed search rules (filters) that automatically apply to every search request, ensuring users only see their own data.", "fetchedAt": "2026-09-06T22:03:27.424Z" }, { "id": "meilisearch-docs-36", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/resources/self_hosting/overview.md", "excerpt": "For production deployments, you will also need: A reverse proxy (Nginx or Caddy) for HTTPS termination A process manager (systemd)... A master key for authentication", "fetchedAt": "2026-09-06T22:03:27.424Z" }, { "id": "meilisearch-docs-37", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/full_text_search/relevancy/typo_tolerance_settings.md", "excerpt": "Typo tolerance helps users find relevant results even when their search queries contain spelling mistakes or typos", "fetchedAt": "2026-09-16T20:42:51.730Z" }, { "id": "meilisearch-docs-38", "tier": "claimed-docs", "url": "https://www.meilisearch.com/docs/capabilities/full_text_search/relevancy/synonyms.md", "excerpt": "you can create a list of synonyms. 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Each sees results ranked by their unique preferences, no extra configuration needed.", "fetchedAt": "2026-09-16T20:42:51.730Z" }, { "id": "meilisearch-docs-49", "tier": "claimed-docs", "url": "https://www.meilisearch.com/solutions/saas", "excerpt": "Tenant tokens restrict search results to a specific tenant. Documents are filtered at query time. No data ever crosses boundaries.", "fetchedAt": "2026-09-16T20:42:51.730Z" }, { "id": "meilisearch-docs-50", "tier": "claimed-docs", "url": "https://www.meilisearch.com/solutions/app-search", "excerpt": "Typed SDKs for JavaScript, Python, Ruby, PHP, Go, Rust, Java, Swift, Dart, and .NET.", "fetchedAt": "2026-09-16T20:42:51.730Z" }, { "id": "meilisearch-docs-51", "tier": "claimed-docs", "url": "https://www.meilisearch.com/solutions/app-search", "excerpt": "Cache results and indexes for offline-first apps. 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Unfortunately indexing performance for constantly changing records wasn't great and Meilisearch would fall behind on indexing for hours; we had to transition to Elastic for our fast-paced ecommerce system.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-5", "tier": "community", "url": "https://news.ycombinator.com/item?id=34707727", "excerpt": "The other issue we faced is their Rails gems falling out of step with the server, and when fixes came out, the Rails gem was incompatible for a while.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-6", "tier": "community", "url": "https://news.ycombinator.com/item?id=34707727", "excerpt": "This is awesome news! We've been using meilisearch in production for a few months now and we're more than happy with its reliability. The search speed and especially indexing speed has increased a lot thanks to their efforts.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-7", "tier": "community", "url": "https://news.ycombinator.com/item?id=34707727", "excerpt": "Very early adopter of meilisearch and it's pretty great. But bumpy as the team found their footing but overall very impressed with it.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-8", "tier": "community", "url": "https://news.ycombinator.com/item?id=34707727", "excerpt": "1. The rules for text searches are too strict by default and if the order of words is different, will result in no matches. 2. Creating an index, uploading documents and changing settings required quite a bit of work, a week's worth of coding. 4. The default number of documents and max uploaded file size is too low, and it fails even on smaller file sizes.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-9", "tier": "community", "url": "https://news.ycombinator.com/item?id=34707727", "excerpt": "Congrats team. Meilisearch is an absolute joy to work with.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-10", "tier": "community", "url": "https://news.ycombinator.com/item?id=22685831", "excerpt": "I'm impressed. Blazing fast to index, like 10x more performant than using ElasticSearch/Searchkick; Blazing fast to search, at least 3x faster; Literally zero config; Uses 140MB of RAM currently, while ElasticSearch would crash with anything less than 1GB.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-11", "tier": "community", "url": "https://news.ycombinator.com/item?id=22685831", "excerpt": "MeiliSearch appears to be more of an alternative to Lucene than it is to Elasticsearch...Absent a similar aggregation layer, MeiliSearch isn't 'elastic' as the comparison implies.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-12", "tier": "community", "url": "https://news.ycombinator.com/item?id=22685831", "excerpt": "The practice itself is malignant [on-by-default analytics]; either explicitly ask upon first run or require an env variable to enable it.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-13", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/22685831", "excerpt": "I've had issues scaling writes to it. You can get around it, but maybe this would be better in a high write environment.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-14", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "We use Meilisearch in production with a 7 million article corpus - it works really well.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-15", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "Running Meilisearch on a Hetzner AX52 (64GB RAM) with ~80,000,000 documents across 13 indexes; searches are fast and it's 'bored' at idle load. Had early hiccups with high CPU during heavy indexing before batch indexing was introduced, which the team helped fix via Discord; now smooth sailing. Would recommend Meilisearch.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-16", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "We needed a 16GB machine to import all the data into Meilisearch, as batch indexing is quite memory intensive, but once it's all indexed we scaled it back to half that RAM and it works great - very performant.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-17", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "Tested Meilisearch recently, was a great experience, getting a multi-index search running in our frontend was very easy. Just wish they had an Australian instance, the closest is Singapore.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-18", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "I installed coolify on a VM and it had a one-click Meilisearch docker install. I sent 1,000,000 records to it and it 'just worked' on a little $8/mo Hetzner instance.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-19", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "Been a happy user of MS in production for notado.app for many years...the older version I'm running is chugging along and doing a great job.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-comm-20", "tier": "community", "url": "https://hn.algolia.com/api/v1/items/43680699", "excerpt": "I recently stood up the server in our k8s cluster and that part was also pretty easy, at least compared to elastic.", "fetchedAt": "2026-09-06T22:05:39.573Z" }, { "id": "meilisearch-probe-1", "tier": "probe", "url": "https://www.meilisearch.com/llms.txt", "excerpt": "PROBE llms.txt: HTTP 200 at https://www.meilisearch.com/llms.txt # Meilisearch — Official Information (llms.txt)\n\nThis file is maintained by **Meilisearch** to help AI assistants, searc", "fetchedAt": "2026-09-16T20:45:59.555Z" }, { "id": "meilisearch-probe-2", "tier": "probe", "url": "https://www.meilisearch.com/docs/getting_started/overview.md", "excerpt": "PROBE docs-md: HTTP 200 at https://www.meilisearch.com/docs/getting_started/overview.md > ## Documentation Index\n> Fetch the complete documentation index at: https://www.meilisearch.com/docs/llms.txt\n> Use th", "fetchedAt": "2026-09-16T20:45:59.555Z" }, { "id": "meilisearch-probe-3", "tier": "probe", "url": "https://www.meilisearch.com/openapi.json", "excerpt": "PROBE openapi: all candidate paths 404 (https://www.meilisearch.com/openapi.json, https://www.meilisearch.com/swagger.json, https://www.meilisearch.com/api/openapi.json, https://www.meilisearch.com/.well-known/openapi.json)", "fetchedAt": "2026-09-16T20:45:59.555Z" }, { "id": "meilisearch-probe-4", "tier": "probe", "url": "https://www.meilisearch.com/docs/getting_started/integrations/mcp", "excerpt": "official MCP server documented at https://www.meilisearch.com/docs/getting_started/integrations/mcp", "fetchedAt": "2026-09-16T20:45:59.555Z" } ]