🎧 Motivation Behind the Project
Modern music streaming services have evolved tremendously — yet, one area still feels incomplete: access to full and rich lyrics for all songs. This gap becomes more visible with indie artists, non-English songs, and unreleased demos, which often lack proper lyric integration.
While some platforms use services like Musixmatch, others such as Genius or Letras.mus.br host a broader variety of lyrical content. However, these platforms are not deeply integrated into most music players today.
This project started with a question:
What if we could enhance the music listening experience by integrating intelligent, fast, and respectful lyric search — using the tools we already have today?
Link:🔗http://localhost:3000/api/auth/login
🔍 The Vision
The project was guided by two main ideas:
User experience in music apps should be contextual, complete, and intelligent.
Lyrics are a core part of how people connect with music. When they’re missing, the experience feels less immersive.
The limitation is not in technology — it’s in integration and licensing decisions.
We already have the tools to build this. What’s missing is the alignment between platforms to make it happen.
⚙️ The Solution
Using Algolia’s MCP Server for fast, scalable search and Google Gemini CLI for smart content handling, this project simulates how a user-friendly lyric search experience could work — one that connects streaming activity with external lyrics platforms, without hosting or displaying copyrighted material directly.
This prototype doesn’t display real-time lyrics (to respect legal boundaries), but it demonstrates the technical feasibility and opens a conversation on what could be built with the right partnerships and permissions.
const algoliasearch = require('algoliasearch');
class AlgoliaService {
constructor() {
this.client = algoliasearch(
process.env.ALGOLIA_APP_ID,
process.env.ALGOLIA_API_KEY
);
this.index = this.client.initIndex('lyrics');
}
async searchLyrics(artist, title) {
try {
const searchQuery = `${artist} ${title}`;
const { hits } = await this.index.search(searchQuery, {
attributesToRetrieve: ['artist', 'title', 'lyrics', 'source', 'url'],
hitsPerPage: 5,
typoTolerance: true,
ignorePlurals: true
});
if (hits.length === 0) {
return null;
}
// Find best match based on artist and title similarity
const bestMatch = this.findBestMatch(hits, artist, title);
if (bestMatch) {
return {
lyrics: bestMatch.lyrics,
source: bestMatch.source || 'Algolia Index',
confidence: bestMatch._score || 0.8,
url: bestMatch.url,
artist: bestMatch.artist,
title: bestMatch.title
};
}
return null;
} catch (error) {
console.error('Algolia search error:', error);
return null;
}
}
findBestMatch(hits, targetArtist, targetTitle) {
let bestMatch = null;
let highestScore = 0;
for (const hit of hits) {
const artistScore = this.calculateSimilarity(
hit.artist?.toLowerCase() || '',
targetArtist.toLowerCase()
);
const titleScore = this.calculateSimilarity(
hit.title?.toLowerCase() || '',
targetTitle.toLowerCase()
);
const totalScore = (artistScore + titleScore) / 2;
if (totalScore > highestScore && totalScore > 0.6) {
highestScore = totalScore;
bestMatch = { ...hit, _score: totalScore };
}
}
return bestMatch;
}
calculateSimilarity(str1, str2) {
// Simple similarity calculation (Levenshtein distance based)
const longer = str1.length > str2.length ? str1 : str2;
const shorter = str1.length > str2.length ? str2 : str1;
if (longer.length === 0) return 1.0;
const distance = this.levenshteinDistance(longer, shorter);
return (longer.length - distance) / longer.length;
}
levenshteinDistance(str1, str2) {
const matrix = [];
for (let i = 0; i <= str2.length; i++) {
matrix[i] = [i];
}
for (let j = 0; j <= str1.length; j++) {
matrix[0][j] = j;
}
for (let i = 1; i <= str2.length; i++) {
for (let j = 1; j <= str1.length; j++) {
if (str2.charAt(i - 1) === str1.charAt(j - 1)) {
matrix[i][j] = matrix[i - 1][j - 1];
} else {
matrix[i][j] = Math.min(
matrix[i - 1][j - 1] + 1,
matrix[i][j - 1] + 1,
matrix[i - 1][j] + 1
);
}
}
}
return matrix[str2.length][str1.length];
}
async indexLyrics(lyricsData) {
try {
const record = {
objectID: `${lyricsData.artist}_${lyricsData.title}`.replace(/[^a-zA-Z0-9]/g, '_'),
artist: lyricsData.artist,
title: lyricsData.title,
lyrics: lyricsData.lyrics,
source: lyricsData.source,
url: lyricsData.url,
indexedAt: new Date().toISOString()
};
await this.index.saveObject(record);
console.log(`✅ Indexed lyrics for: ${lyricsData.artist} - ${lyricsData.title}`);
return true;
} catch (error) {
console.error('Algolia indexing error:', error);
return false;
}
}
async batchIndexLyrics(lyricsArray) {
try {
const records = lyricsArray.map((lyrics, index) => ({
objectID: `${lyrics.artist}_${lyrics.title}`.replace(/[^a-zA-Z0-9]/g, '_'),
artist: lyrics.artist,
title: lyrics.title,
lyrics: lyrics.lyrics,
source: lyrics.source || 'Batch Import',
url: lyrics.url,
indexedAt: new Date().toISOString()
}));
await this.index.saveObjects(records);
console.log(`✅ Batch indexed ${records.length} lyrics`);
return true;
} catch (error) {
console.error('Algolia batch indexing error:', error);
return false;
}
}
}
module.exports = new AlgoliaService();
🧠 What the Code Does
This class, AlgoliaService, wraps around Algolia's SDK to handle three key functions:
Search for lyrics by artist and title
Find the best match based on similarity
Index new lyrics (single or batch)
✅Key Takeaways
There is a real user need for richer, more complete lyric integration in music apps.
The gap is not due to missing technology — it’s a matter of platform decisions and licensing agreements.
Algolia MCP can act as a powerful bridge to simulate a better search experience, enhancing what’s possible within legal and ethical limits.
AI tools like Gemini can streamline development, making intelligent integration faster and more adaptive.
Top comments (3)
Good idea! Even though the project isn't implemented yet, the concept sounds promising.
Would be interesting to see it in action once you build it out.
Thank you!
Awesome concept! I'd recommend deploying it somewhere easily accessible and testable because it would be really cool to see this idea with a nice front end
Thanks for sharing