ZBS Index What actually exists in applied AI, with the source next to it

mcp server

market

Search and get fashion products recommendations across multiple e-ecom stores

Description as published by the maintainer. Source

  • version 1.0.0
  • slowing
  • retrieval

slowing — Registry entry last updated 2026-04-11. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.

What this server can do

6 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

discover_brands(limit, query, style, country, price_tier, gender_focus, category_focus, ships_from_country)
Find fashion brands using natural language, structured filters, or both. Best for queries like "Italian streetwear brands", "Scandinavian minimalist brands", "Japanese technical outerwear", "brands with avant-garde tailoring", or qualified similarity such as "brands like Rick Owens for technical outerwear". For a plain "brands like X" request, use find_similar_brands. Country adjectives ("Italian", "Scandinavian", "Nordic", "Japanese", "Iberian", "Benelux") are parsed server-side into shipping-origin filters; you don't need to translate them to ISO codes. `query` is optional — provide a query, structured filters, or both. Brand country/shipping signals are best-effort and separate from product availability.
discover_products(page, brand, limit, query, colors, gender, season, styles, country, pattern, sleeves, category, currency, neckline, occasion, materials, max_price, min_price, silhouette, color_match, store_domain, exclude_colors, is_sustainable, available_sizes, exclude_materials)
Find fashion products using natural language and/or structured filters. Provide a `query` for semantic ranking via multimodal text+image embeddings ("oversized wool coat", "black leather jacket", "minimalist gold jewelry", "linen shirt for a beach wedding under $200") — best for open-ended discovery. Keep queries concrete: noun-led with up to one or two modifiers works best ("summer linen shirt" beats "breathable linen shirt perfect for summer"). Provide only structured filters (category, brand, colors, gender, price, etc.) for pure browse — results are recency-ranked and paginate cleanly. Combine both for filtered semantic search. At least one of query or a filter must be provided. Example calls (notice the sparse filter population — descriptive attributes stay in `query`, not in structured fields): - "linen wedding guest dress under $200" → {query: "linen wedding guest dress", gender: "women", max_price: 200, materials: ["linen"]} - "wool coat under $300" → {query: "wool coat", gender: "women", max_price: 300, materials: ["wool"]} - "browse women's black dresses $100-$300" → {gender: "women", category: "clothing/dresses", colors: ["black"], min_price: 100, max_price: 300} - "Acne Studios outerwear" → {query: "outerwear", brand: "Acne Studios", gender: "women"} Returns compact product cards: AI-generated summary, price, images, tags, and compact availability by color/size; variant price differences are nested under the availability dimension that determines price. For merchant description, store info, SKU-level variants, exact variant prices, and all product images, call get_product with a product ID from these results. Multi-currency prices supported (e.g. "under 200 zł" or min_price=200 + currency="PLN"); returned prices render in the requested currency when provided.
find_similar_brands(brand, limit, country)
Given an active catalog brand name or merged alias, find similar brands using brand-profile vectors generated during product indexing. Unknown or ambiguous seeds return no brands. Returns up to 20 brands. Required: brand.
find_similar_products(page, limit, country, currency, product_id)
Given a product ID, find similar products across the entire catalog. Useful for "more like this" recommendations or finding alternatives. Returns compact product cards, not full variant detail; call get_product for SKU-level variants, exact variant prices, merchant description, store info, and all images. Returns page and hasNextPage. Returns up to 20 results per page, paginated (max 3 pages). Required: product_id.
get_filters(fields, gender, country, brand_page, brand_search)
Returns available filter values in the catalog. By default returns categoryTree plus brands, colors, materials, genders, occasions, seasons, styles, silhouettes, currencies, and price range. Use "fields" to request only specific dimensions — faster and less data. "categoryTree" is a flat DFS-ordered list of { value, label } entries; hierarchy is encoded in the value slug (e.g. "clothing/jackets/bomber-jackets"), parents appear before descendants, and every value can be passed directly to discover_products.category. Use "brand_search" to search brands by prefix instead of listing all. Pass "gender" to scope categoryTree to that gender (women/men/girls/boys); omit to see the merged union.
get_product(country, currency, product_id)
Get the detailed response for a specific product ID. Use this after discover_products or find_similar_products when you need merchant description, store info, all images, SKU-level availability variants, SKU, colorKey/size matrix, exact variant prices/compareAtPrice in the requested currency, and the direct link to purchase. Required: product_id.

Last successful function declaration observed on . Source: https://api.vistoya.com/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://api.vistoya.com/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
Latest published version 1.0.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-04-11 When the registry record was last updated by its maintainer. point in time Model Context Protocol
First listed in the MCP Registry 2026-04-11 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
mcp tools declared 6 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe api.vistoya.com
mcp endpoint status ok The server listed 6 functions when asked. as of probe api.vistoya.com

Where to get it

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

GET /api/v1/entries/mcp_server.json

Sources

  1. Tools declared by the MCP server at https://api.vistoya.com/mcp — api.vistoya.com, observed , trust tier 4.
  2. Official MCP Registry — Model Context Protocol, observed , trust tier 1.