The browsing history endpoints let clients record and retrieve the records a user has viewed. The history is capped at 10 unique items per user — when a new item is added and the cap is reached, the oldest entry is evicted (FIFO). DuplicateDocumentation Index
Fetch the complete documentation index at: https://mintlify.com/akibanks/api-tienda-vinilos/llms.txt
Use this file to discover all available pages before exploring further.
discogs_id values are upserted: if the release is already in the user’s history, the server updates its visto_en timestamp instead of creating a duplicate row.
POST /historial
Record a vinyl release that the authenticated user has just viewed.| Method | POST |
| Path | /historial |
| Auth | JWT required (Authorization: Bearer <token>) |
Request body
The Discogs release ID for the viewed record (e.g.
"249504").Title of the vinyl release as returned by the Discogs API.
Artist name for the release.
Primary genre of the release (e.g.
"Rock", "Jazz"). Used to power personalised recommendations — omitting it degrades recommendation quality.Primary style sub-tag of the release (e.g.
"Classic Rock", "Bebop").Responses
201 — History updatedExample
GET /historial
Retrieve the authenticated user’s browsing history, sorted from most recently viewed to oldest.| Method | GET |
| Path | /historial |
| Auth | JWT required (Authorization: Bearer <token>) |
Request params
No query parameters. The user is identified entirely from the JWT payload.Response
Returns a JSON array of up to 50 history objects, ordered newest first.Primary key of the history row.
ID of the user who viewed the record.
Discogs release ID of the viewed record.
Title of the release.
Artist name of the release.
Genre recorded at view time.
null if not supplied when the history entry was created.Style sub-tag recorded at view time.
null if not supplied.ISO 8601 datetime of the most recent view (e.g.
"2024-11-03T18:45:00.000Z").Example
Although the store caps history at 10 items per user,
GET /historial returns up to 50 records. This higher limit accommodates history rows that existed before the per-user cap was introduced, ensuring no legacy data is silently dropped.