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Build Status Dependency status License Slack Bors enabled

Lightning Fast, Ultra Relevant, and Typo-Tolerant Search Engine 🔍

Meilisearch is a powerful, fast, open-source, easy to use and deploy search engine. Both searching and indexing are highly customizable. Features such as typo-tolerance, filters, and synonyms are provided out-of-the-box. For more information about features go to our documentation.

Web interface gif


  • Search-as-you-type experience (answers < 50 milliseconds)
  • Full-text search
  • Typo tolerant (understands typos and misspelling)
  • Faceted search and filters
  • Supports hanzi (Chinese characters)
  • Supports synonyms
  • Easy to install, deploy, and maintain
  • Whole documents are returned
  • Highly customizable
  • RESTful API

Getting started

Deploy the Server

Homebrew (Mac OS)

brew update && brew install meilisearch


docker run -p 7700:7700 -v "$(pwd)/meili_data:/meili_data" getmeili/meilisearch

Announcing a cloud-hosted Meilisearch

Join the closed beta by filling out this form.

Try Meilisearch in our Sandbox

Create a Meilisearch instance in Meilisearch Sandbox. This instance is free, and will be active for 48 hours.

Run on Digital Ocean

DigitalOcean Marketplace

Deploy on

Deploy on

APT (Debian & Ubuntu)

echo "deb [trusted=yes] /" > /etc/apt/sources.list.d/fury.list
apt update && apt install meilisearch-http

Download the binary (Linux & Mac OS)

curl -L | sh

Compile and run it from sources

If you have the latest stable Rust toolchain installed on your local system, clone the repository and change it to your working directory.

git clone
cd meilisearch
cargo run --release

Create an Index and Upload Some Documents

Let's create an index! If you need a sample dataset, use this movie database. You can also find it in the datasets/ directory.

curl -L -o movies.json

Now, you're ready to index some data.

curl -i -X POST '' \
  --header 'content-type: application/json' \
  --data-binary @movies.json

Search for Documents

In command line

The search engine is now aware of your documents and can serve those via an HTTP server.

The jq command-line tool can greatly help you read the server responses.

curl '' | jq
  "hits": [
      "id": "415",
      "title": "Batman & Robin",
      "poster": "",
      "overview": "Along with crime-fighting partner Robin and new recruit Batgirl, Batman battles the dual threat of frosty genius Mr. Freeze and homicidal horticulturalist Poison Ivy. Freeze plans to put Gotham City on ice, while Ivy tries to drive a wedge between the dynamic duo.",
      "release_date": 866768400
      "id": "411736",
      "title": "Batman: Return of the Caped Crusaders",
      "poster": "",
      "overview": "Adam West and Burt Ward returns to their iconic roles of Batman and Robin. Featuring the voices of Adam West, Burt Ward, and Julie Newmar, the film sees the superheroes going up against classic villains like The Joker, The Riddler, The Penguin and Catwoman, both in Gotham City… and in space.",
      "release_date": 1475888400
  "nbHits": 8,
  "exhaustiveNbHits": false,
  "query": "botman robin",
  "limit": 2,
  "offset": 0,
  "processingTimeMs": 2

Use the Web Interface

We also deliver an out-of-the-box web interface in which you can test Meilisearch interactively.

You can access the web interface in your web browser at the root of the server. The default URL is All you need to do is open your web browser and enter Meilisearch’s address to visit it. This will lead you to a web page with a search bar that will allow you to search in the selected index.

| See the gif above


Now that your Meilisearch server is up and running, you can learn more about how to tune your search engine in the documentation.


Hey! We're glad you're thinking about contributing to Meilisearch! Feel free to pick an issue labeled as good first issue, and to ask any question you need. Some points might not be clear and we are available to help you!

Also, we recommend following the CONTRIBUTING to create your PR.

Core engine and tokenizer

The code in this repository is only concerned with managing multiple indexes, handling the update store, and exposing an HTTP API.

Search and indexation are the domain of our core engine, milli, while tokenization is handled by our tokenizer library.


Meilisearch collects anonymous data regarding general usage. This helps us better understand developers' usage of Meilisearch features.

To find out more on what information we're retrieving, please see our documentation on Telemetry.

This program is optional, you can disable these analytics by using the MEILI_NO_ANALYTICS env variable.

Feature request

The feature requests are not managed in this repository. Please visit our dedicated repository to see our work about the Meilisearch product.

If you have a feature request or any feedback about an existing feature, please open a discussion. Also, feel free to participate in the current discussions, we are looking forward to reading your comments.

💌 Contact

Please visit this page.

Meilisearch is developed by Meili, a young company. To know more about us, you can read our blog. Any suggestion or feedback is highly appreciated. Thank you for your support!