Remote MCP server to run your Atako AI agents: chat, projects, files, integrations and channels.
- Passed: Handshake
- Passed: Tools listed
- Passed: Updated recently
Median latency 132 ms · Last checked
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Evidence for your next connection.
Independent measurements of remote MCP servers. Every observation has a timestamp.
Read-only probesMCP server · Code & DevOps
Search and get fashion products recommendations across multiple e-ecom stores
1 failed · 8 not measured
Median of successful probes over 7 days
Share of countable probes over 30 days, including daily rollups. Auth challenges are excluded.
Tool definitions returned by this server
Independent monitoring
Responded
The server completed its last measured handshake. This is an observation, not a guarantee.
Last checked| Test area | Passed | Failed | Unmeasured |
|---|---|---|---|
ConnectionCan a client connect and discover tools? | 5 | 0 | 0 |
Reliability & speedDoes it respond consistently and quickly? | 0 | 0 | 4 |
Access & authenticationWhat is required to use this server? | 1 | 0 | 2 |
Tool qualityAre the tool definitions usable by an agent? | 4 | 0 | 0 |
Publisher identityCan the publisher be traced to its source? | 3 | 1 | 2 |
Unmeasured means there is not enough evidence to decide. How these checks work
Start using io.github.vistoya/market
Choose your client, copy the configuration, then enable the server in your client’s MCP settings.
Run this command in your terminal, then restart Claude Code.
Claude Code
claude mcp add --transport http io-github-vistoya-market https://api.vistoya.com/mcpCapabilities
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.
DiscoveredFind 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.
DiscoveredGiven 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.
DiscoveredGiven 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).
DiscoveredReturns 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.
DiscoveredGet 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.
DiscoveredRecent measurements
| Checked | Result | Response | Tools |
|---|---|---|---|
| Connected | 412 ms | 6 |