# Spotify Search Scraper (`powerai/spotify-search-scraper`) Actor
Search Spotify by keyword and category, collecting results metadata with rich fields for analysis, discovery, and research.
- **URL**: https://apify.com/powerai/spotify-search-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** Social media, Other, Integrations
- **Stats:** 3 total users, 2 monthly users, 80.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.99 / 1,000 results
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## ๐ง Spotify Playlist Search Scraper
Search Spotify playlists by keyword and collect playlist metadata for analysis, discovery, and research. Each scraped playlist record includes a `scrapedAt` timestamp so you can track when the data was retrieved.
### โจ What You Get
- ๐ต Playlist results from your search keyword (`q`)
- ๐งพ Rich playlist metadata (for example: `uri`, `name`, `description`)
- ๐ผ๏ธ Optional image information for the playlist
- ๐ค Owner information
- ๐ง Structured JSON output ready for downstream processing
### ๐ฏ Good For
- Content discovery and recommendation research
- Music/genre trend exploration
- Competitive playlist benchmarking
- Building searchable datasets for analytics
- Curator workflows and playlist dataset enrichment
### ๐ Input
| Parameter | Required | Description |
|-----------|----------|-------------|
| `q` | Yes | Search keyword (for example: `pop`, `hip hop`, `workout`). |
| `maxResults` | No | Maximum number of playlists to collect (default: `30`). |
| `gl` | No | Optional region code to influence search results (for example: `US`). |
| `type` | No | Search result category (allowed values: `albums`, `artists`, `episodes`, `genres`, `playlists`, `podcasts`, `tracks`, `users`). Defaults to `playlists`. |
#### Input Example
```json
{
"q": "pop",
"maxResults": 30,
"type": "playlists"
"gl": "US"
}
````
### ๐ฆ Output
The actor returns a dataset of playlist records. Each record is a JSON object containing playlist fields plus `scrapedAt`.
#### Output Example
```json
[
{
"uri": "spotify:playlist:37i9dQZF1EQncLwOalG3K7",
"name": "Pop Mix",
"description": "The Chainsmokers, ...",
"images": {
"items": [
{
"sources": [
{ "url": "https://pickasso.spotifycdn.com/image/...", "width": null, "height": null }
]
}
]
},
"owner": { "name": "Spotify" },
"scrapedAt": "2026-03-23T06:40:35.280Z"
}
]
```
# Actor input Schema
## `q` (type: `string`):
Keyword to search for Spotify playlists (e.g. pop, hip hop, workout).
## `maxResults` (type: `integer`):
Maximum number of playlists to collect.
## `gl` (type: `string`):
Optional region code to influence the search results (e.g. US, GB, DE).
## `type` (type: `string`):
Choose the search result category. Allowed values: albums, artists, episodes, genres, playlists, podcasts, tracks, users.
## Actor input object example
```json
{
"q": "pop",
"maxResults": 30,
"gl": "US",
"type": "playlists"
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"q": "pop",
"maxResults": 30,
"gl": "US"
};
// Run the Actor and wait for it to finish
const run = await client.actor("powerai/spotify-search-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"q": "pop",
"maxResults": 30,
"gl": "US",
}
# Run the Actor and wait for it to finish
run = client.actor("powerai/spotify-search-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"q": "pop",
"maxResults": 30,
"gl": "US"
}' |
apify call powerai/spotify-search-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=powerai/spotify-search-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Spotify Search Scraper",
"description": "Search Spotify by keyword and category, collecting results metadata with rich fields for analysis, discovery, and research.",
"version": "0.0",
"x-build-id": "gMQQuA6N8KOaMj5le"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/powerai~spotify-search-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-powerai-spotify-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/powerai~spotify-search-scraper/runs": {
"post": {
"operationId": "runs-sync-powerai-spotify-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/powerai~spotify-search-scraper/run-sync": {
"post": {
"operationId": "run-sync-powerai-spotify-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"q"
],
"properties": {
"q": {
"title": "Search Query",
"type": "string",
"description": "Keyword to search for Spotify playlists (e.g. pop, hip hop, workout).",
"default": "pop"
},
"maxResults": {
"title": "Maximum Results",
"minimum": 20,
"maximum": 5000,
"type": "integer",
"description": "Maximum number of playlists to collect.",
"default": 30
},
"gl": {
"title": "Region",
"type": "string",
"description": "Optional region code to influence the search results (e.g. US, GB, DE).",
"default": "US"
},
"type": {
"title": "Search Type",
"enum": [
"albums",
"artists",
"episodes",
"genres",
"playlists",
"podcasts",
"tracks",
"users"
],
"type": "string",
"description": "Choose the search result category. Allowed values: albums, artists, episodes, genres, playlists, podcasts, tracks, users.",
"default": "playlists"
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```