Meilisearch Documentation llms.txt · AI Docs Browser · mdream [llms.txt Tools](https://mdream.dev/llms-txt/meilisearch/llms-txt) # Meilisearch Documentation llms.txt docs.meilisearch.com/llms.txt [Raw llms.txt](https://docs.meilisearch.com/llms.txt) [Raw llms-full.txt](https://docs.meilisearch.com/llms-full.txt) Copy Markdown [](https://docs.meilisearch.com/llms.txt) llms.txt Docs Analytics metrics reference Analytics events endpoint Migrate to the November 2025 Meilisearch Cloud analytics Configure analytics events Bind search analytics events to a user Exclude search requests from analytics Track click events Track conversion events Analytics Chat tooling reference Reduce hallucination Build a chat interface Generate summarized answers Set up conversational search Configure a chat workspace Configure guardrails Configure index chat settings Display source documents Handle errors and fallbacks Optimize chat prompts Stream chat responses What is conversational search? Build disjunctive facets Filter expression reference Foreign filters Optimize facet performance Precise filtering with array relationships Filter search results Build faceted navigation Combine filters and sort Configure granular filterable attributes Search within facet values Filtering and sorting by date Search with facets Handle large facet cardinality Search and filter together Sort search results Filtering, sorting, and faceting Debug search performance Performance tuning Ranking pipeline Your first search Phrase search Placeholder search Search with snippets Configure a custom dictionary Configure displayed attributes Configure distinct attribute Configure prefix search Configure search cutoff Configure searchable attributes Configure stop words Highlight search results Paginate search results Use matching strategy Full-text search Attribute ranking order Custom ranking rules Built-in ranking rules Ranking score Relevancy Synonyms Typo tolerance Geosearch Filter by geo bounding box Filter by geo polygon Filter by geo radius Sort by geo point Use GeoJSON format Geo search Binary quantization Composite embedders Custom hybrid ranking Document template best practices Multiple embedders Semantic vs hybrid search Tune the distribution of semantic scores Getting started with AI-powered search Which embedder should I choose? Configure Cohere embedder Configure HuggingFace embedder Configure OpenAI embedder Configure a REST embedder Image search with multimodal embeddings Image search with user-provided embeddings Use AI-powered search with user-provided embeddings Hybrid and semantic search Semantic Search with AWS Bedrock Embeddings Semantic Search with Cloudflare Workers AI Embeddings Semantic Search with Gemini Embeddings Semantic Search with Hugging Face Inference Endpoints Semantic Search with Jina Embeddings Semantic Search with Mistral Embeddings Semantic Search with Voyage AI Embeddings Indexing best practices Tokenization Getting started with indexing Add and update documents Compact an index Delete documents at scale Design primary keys Document relations Edit documents with functions Export data to another instance Handling multilingual datasets Import large datasets Define index relationships Indexing Tasks and asynchronous operations Filtering tasks Managing the task database Working with tasks Optimize indexing performance with batch statistics Federated search Multi-index search Boost results across indexes Build a unified search bar Combine text and image search Search with different filters per index Multi-search Capabilities overview Performing personalized search queries Building recommendations with similar documents Generate user context Personalize ecommerce search Personalization and recommendations Invoices Billing Payment methods Pricing model Backups Create a project Manage resources Cloud infrastructure Cloud regions Sharding and replication Version management Experimental features Project management Webhooks Indexing performance Monitoring Prometheus endpoint Search performance Operations Meilisearch Cloud platform Getting started with teams Configure SSO Manage team roles Meilisearch Cloud teams Search rule behavior Getting started with search rules Curate default results for an empty query List or filter existing rules Pause a rule without deleting it Pin several results in a fixed order Pin one result for a query Schedule a promotion for a limited time Search rules Role-based access control with joins Tenant token payload reference Multitenancy and tenant tokens Generate a tenant token without a library Generate tenant tokens without a Meilisearch SDK Manage API keys Security and tenant tokens Changelog Features First Project Laravel Scout guide Ruby on Rails quick start Strapi v4 guide Symfony Glossary Good practices Integrate a relevant search bar to your documentation Instant-meilisearch React quick start Vue quick start Firebase Connect Amazon S3 to Meilisearch with Kestra Migrate Elasticsearch to Meilisearch with Kestra Connect Kafka to Meilisearch with Kestra Connect MongoDB to Meilisearch with Kestra Migrate OpenSearch to Meilisearch with Kestra Sync data to Meilisearch with Kestra Connect PostgreSQL to Meilisearch with Kestra Connect RabbitMQ to Meilisearch with Kestra Connect a REST API to Meilisearch with Kestra Connect Shopify to Meilisearch with Kestra LangChain integration Model Context Protocol (MCP) Meilisearch Importer Postman collection for Meilisearch Integrate Meilisearch Cloud with Vercel Welcome to Meilisearch Dart quick start .NET quick start Go quick start Java quick start JavaScript quick start PHP quick start Python quick start Ruby quick start Rust quick start Swift quick start tasks Compact task queue tasks asynchronous operations task task asynchronous operations asynchronous operations Authorization dump directory Create snapshot Delete a chat workspace Get a chat workspace Get settings of a chat workspace List chat workspaces Request a chat completion Reset the settings of a chat workspace Update settings of a chat workspace Add or replace documents Add or update documents Delete all documents primary key primary key Delete documents by filter RHAI function primary key List documents with GET List documents with POST Configure experimental features Configure network topology Get network topology List experimental features Network control Export to a remote Meilisearch Search for facet values Headers Get health Compact index primary key Delete index primary key Get stats of index List all indexes List index fields Swap indexes primary key Create API key Delete API key Get API key List API keys Update API key Retrieve logs Stop retrieving logs Update target of the console logs Perform a multi-search OpenAPI specifications Pagination Requests Create or update a search rule Delete a search rule Get a search rule List search rules Search with GET Search with POST Get chat Get dictionary Get displayedAttributes Get distinctAttribute Get embedders Get faceting Get facetSearch Get filterableAttributes Get foreignKeys Get localizedAttributes Get nonSeparatorTokens Get pagination Get prefixSearch Get proximityPrecision Get rankingRules Get searchableAttributes Get searchCutoffMs Get separatorTokens Get sortableAttributes Get stopWords Get synonyms Get typoTolerance List all settings Reset all settings Reset chat Reset dictionary Reset displayedAttributes Reset distinctAttribute Reset embedders Reset faceting Reset facetSearch Reset filterableAttributes Reset foreignKeys Reset localizedAttributes Reset nonSeparatorTokens Reset pagination Reset prefixSearch Reset proximityPrecision Reset rankingRules Reset searchableAttributes Reset searchCutoffMs Reset separatorTokens Reset sortableAttributes Reset stopWords Reset synonyms Reset typoTolerance Update all settings Update chat Update dictionary Update displayedAttributes Update distinctAttribute Update embedders Update faceting Update facetSearch Update filterableAttributes Update foreignKeys Update localizedAttributes Update nonSeparatorTokens Update pagination Update prefixSearch Update proximityPrecision Update rankingRules Update searchableAttributes Update searchCutoffMs Update separatorTokens Update sortableAttributes Update stopWords Update synonyms Update typoTolerance Get similar documents with GET Get similar documents with POST experimental feature Get stats of all indexes Render documents with POST Get version Create webhook Delete webhook Get webhook List webhooks Update webhook Error codes Errors Meilisearch vs Algolia Comparison to alternatives Meilisearch vs Elasticsearch Meilisearch vs MongoDB Atlas Search Meilisearch vs OpenSearch Meilisearch vs Pinecone Meilisearch vs PostgreSQL search Meilisearch vs Qdrant Meilisearch vs Typesense E-commerce Federated Search Image Search Geosearch Home Booking Hydration MoMA Collection Music Search Nobel Prizes Demos Personalized Search Search Playground RubyGems Finder SaaS CRM Search Tenant Tokens Typo Tolerance Voice Search Where to Watch Carbon footprint of Meilisearch Cloud regions Contributing to our documentation Experimental features overview FAQ Known limitations Language Official SDKs and libraries Telemetry Versioning policy Bucket sort Concatenated and split queries Data types Documents Vector storage: DiskANN Indexes Prefix search Primary key Meilisearch ranking: a multi-criteria system beyond BM25 Storage Typo tolerance vs fuzzy search: how Meilisearch handles misspellings Migrating from Algolia to Meilisearch Migrating from Elasticsearch to Meilisearch Migrating to Meilisearch Cloud Migrating from MongoDB Atlas Search to Meilisearch Migrating from PostgreSQL full-text search to Meilisearch Accessing previous docs versions Migrating from Qdrant to Meilisearch Migrating from Supabase full-text search to Meilisearch Update to the latest Meilisearch version Configure Meilisearch at launch Configuration reference Exporting and importing dumps Backing up Meilisearch data Exporting and using Snapshots Deploy on AWS Deploy on DigitalOcean Deploy on Google Cloud Deploying Meilisearch Running Meilisearch in production Enterprise and Community editions Using Meilisearch with Docker Install Meilisearch locally Getting started with self-hosted Meilisearch Search preview Computing Hugging Face embeddings with the GPU Self-hosting Meilisearch Impact of RAM and multi-threading on indexing performance Securing your project Using HTTP/2 and SSL with Meilisearch Master key and API keys Securing self-hosted Meilisearch Protected and unprotected Meilisearch projects Resetting the master key Configure replication for high availability Manage the network Replication and sharding Set up a sharded cluster Using task webhooks OpenAPI Specs meilisearch-openapi meilisearch-openapi-mintlify package package-lock docs-scraper.config videogames stories restaurants movies kitchenware crm-tickets crm-profiles crm-chats books .code-samples.meilisearch ## What is Meilisearch Documentation's llms.txt? Meilisearch Documentation publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Meilisearch Documentation offers and where to find details. Pass Spec 2 Sections 452 Links 93.1 KB Size ~23.8k Tokens Sections: Docs · OpenAPI Specs ## Add Meilisearch Documentation Docs to Your AI Assistant Select your tool to see how to add Meilisearch Documentation's llms.txt as a documentation source. Cursor Windsurf Claude Code ChatGPT Zed Copilot 1. 1 Open any chat or composer panel 2. 2 Type @Docs and select "Add new doc" 3. 3 Paste the URL: https://docs.meilisearch.com/llms.txt 4. 4 Wait for the green dot (indexing complete) 5. 5 Reference @Docs in chat when asking about Meilisearch Documentation Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too. ## Spec Compliance 4 notes ## Frequently Asked Questions Where is Meilisearch Documentation's llms.txt file? Meilisearch Documentation publishes its llms.txt at https://docs.meilisearch.com/llms.txt. This file provides a structured, markdown-formatted index of Meilisearch Documentation's documentation that AI systems can consume to understand the project's APIs, guides, and references. How do I use Meilisearch Documentation's llms.txt with AI coding assistants? Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Meilisearch Documentation's documentation so it can provide better code suggestions and answers about Meilisearch Documentation. What does Meilisearch Documentation's llms.txt contain? Meilisearch Documentation's llms.txt contains 2 sections and 452 documentation links in 93.1 KB (~23.8k tokens). Key sections include Docs, OpenAPI Specs. How many tokens does Meilisearch Documentation's llms.txt use? The concise llms.txt index is approximately 23.8k tokens (93.1 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline. Can I generate an llms.txt for my own project? Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator. ## Browse More llms.txt Files [Inspira UI Inspira UI is a free and open-source Vue.js component library that provides a collection of beautiful and customizable components for building modern web applications.](https://mdream.dev/llms-txt/meilisearch/llms-txt/inspira-ui) [HTTP/3 explained A document describing the HTTP/3 and QUIC protocols](https://mdream.dev/llms-txt/meilisearch/llms-txt/http3-explained) [ReadMe Documentation](https://mdream.dev/llms-txt/meilisearch/llms-txt/readme) [Temporal Platform Documentation Build invincible applications](https://mdream.dev/llms-txt/meilisearch/llms-txt/temporal) [cohere](https://mdream.dev/llms-txt/meilisearch/llms-txt/cohere) [--banner:js hack from https://github.com/evanw/esbuild/pull/2067 You can progressively stream response payloads through Lambda function URLs, including as an Amazon CloudFront origin, along with using the AWS SDK or using Lambda’s invoke API. You can not use Amazon API Gateway and Application Load Balancer to progressively stream response payloads, but you can use the functionality to return larger payloads. (https://aws.amazon.com/blogs/compute/introducing-aws-lambda-response-streaming/)](https://mdream.dev/llms-txt/meilisearch/llms-txt/middy) [Tinybird](https://mdream.dev/llms-txt/meilisearch/llms-txt/tinybird) [Coolify Open Source PaaS](https://mdream.dev/llms-txt/meilisearch/llms-txt/coolify) [View all 99 projects ](https://mdream.dev/llms-txt/meilisearch/llms-txt) ## Related Tools [

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