How to add search to your static site

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Static websites are popular nowadays. There are many static site generators, but not all have search built-in. Recently I’ve added a static search option to a few websites, including the one you’re reading. In this article I would like to share how I did this, as it might take less efforts than you think!

When searching to find a good library for a static full-text search, I came across popular solutions such as Lunr.js, FlexSearch and Fuse.js. To my surprise, these libraries are not very well maintained anymore, while they all have quite some open issues. To me, this does not relate to the popularity of static websites in general.

I’ve used Fuse.js before to implement a simple but fast search engine (on, but this was over a year ago, and I’m always looking for better options. I’ve tried them all again, and each still has at least a few minor glitches. Another reason is that both markdown-rambler and this website itself use ES Modules and other modern JavaScript features, which usually improves developer experience, maintenance and/or performance.


Later, I was lucky enough to find MiniSearch when looking for “search index” in the npm registry. This package happens to be easy to use, while performance and file size feel good. To be honest, I didn’t do an actual file size and performance comparison between the various options, but this MiniSearch blogpost has a good overview.

The fuzzy search and prefix search are optional, and work very well for the websites where I integrated it. This always requires a bit of fine-tuning, depending on the size and density of documents. I did not try the auto-suggestion feature yet. Overall a pleasant experience, much like the alternatives. What stood out initially, was simply better search results.

In my experience so far, the contents of Markdown documents can be used just fine as input for the index. The minimal syntax of Markdown does not seem to negatively impact the index. This makes solutions like MiniSearch great for static websites, as they are often powered by Markdown files.

Getting started

So, how to integrate MiniSearch in your static website? There are roughly four steps here:

  1. Build the index
  2. Serve the index with the rest of the static site
  3. Connect the index with a DOM element (such as an input field)
  4. Search and render results

Building the index

Here’s a fragment from markdown-rambler, but the concept can be applied in any JavaScript build system. The idea is to map existing files or pages to be indexed to an object containing the data necessary for both the index and the fields to eventually be displayed in the search results.

The result (documents) can be provided to a MiniSearch instance using minisearch.addAll(documents), which creates and returns the actual index. The final step here is to store this JSON file to disk:

const documents = files
.filter(files => file.type === 'article')
.map((file, index) => ({
id: index,
const miniSearch = new MiniSearch({
fields: ['title', 'content'],
storeFields: ['title', 'pathname'],
await miniSearch.addAllAsync(documents);
await fs.writeFile('search-index.json', JSON.stringify(miniSearch.toJSON()));

This example uses the title and content fields of each document to index the full-text search. The title and pathname (storeFields) will be available to render the search results later.

Serving the index

Next step is to make sure the index is served with the rest of the static website. This could be the root of the “dist” or “public” folder.

Connecting the search component

Depending on the requirements and the type of (static) website, the next part could be implemented in many ways. Here I’m going to try and keep it very concise. Let’s add search.js to the static site with the following snippet. This will attach an event listener to an existing <input type="search"> in the DOM:

(async () => {
await import('');
const searchIndex = await fetch('/search-index.json').then(response => response.text() );
const index = MiniSearch.loadJSON(searchIndex, { fields: ['title', 'content'] });
const input = document.querySelector('input[type=search]');
const search = query => {
const results =, { prefix: true, fuzzy: 0.3 });
input.addEventListener('input', event => {

Here we already have the basics of our search component, in only a few lines of code. Note that the indexed fields title and content should be provided again when loading the index. For brevity, this example logs the search results in the browser console. Combined with very little styling, this is everything this website uses for the static search.

Searching and rendering results

How to render search results depends on the type of static website or which framework is being used. For the sake of completeness, here’s a minimal example using vanilla JavaScript. This extends the search function from the previous example:

const container = document.createElement('div');
container.setAttribute('id', 'search-results');
const search = query => {
if (query.length > 1) {
const results =, { prefix: true, fuzzy: 0.3 });
const list = document.createElement('ol');
results.slice(0, 10).forEach(result => {
const item = document.createElement('li');
const link = document.createElement('a');
link.setAttribute('href', result.pathname);
} else {

This is roughly the code used on this website, and appends a container element to the DOM as a sibling of the input element. This way, the search results can be rendered relative to this input field.

The search results (with the title and pathname fields we stored in the index before) are appended the container element as an ordered list. Ordered, since MiniSearch provides the results sorted by relevance score.

Final notes


If you are using React, you might be interested in react-minisearch, providing React integration for MiniSearch.

Index size

The search index is a relatively large static asset, as it includes both the index and the data to show in the search results. Loading this file on page load, as shown above, could degrade the performance of your website. It does not block the main render thread as it uses a dynamic import, but for larger websites this may impact overall performance. One way to mitigate this is to only load the index when the user actually uses the search, for instance on the focus event of the input field. To get an idea of the file size, currently the index of this website with its first 11 articles, the size is 113Kb uncompressed, and 20Kb gzipped. This is generally not really an issue, but definitely something to keep an eye on when a website is large or growing. After the first load, the browser will cache the static search index on subsequent page loads.

Multiple search indices

Depending of the site contents, another interesting feature might be to create multiple indices. This would be straight-forward following the steps in this article.