{
  "markdown": "# Vistoya MCP\n\nSemantic search and recommendations across fashion stores, exposed as a Model Context Protocol server. Connect any MCP-compatible AI agent (Claude, Cursor, VS Code, ChatGPT, etc.) and let it discover products, find visually similar items, and explore stores in the Vistoya marketplace.\n\n- **Registry name:** `io.github.vistoya/market`\n- **Endpoint:** `https://api.vistoya.com/mcp`\n- **Transport:** Streamable HTTP\n- **Website:** https://vistoya.com\n\n## Quick setup\n\n```sh\nnpx @vistoya/mcp\n```\n\nAutomatically detects and configures Claude Desktop, Claude Code, Cursor, Windsurf, and VS Code. Restart your AI client after running.\n\n## What it does\n\nVistoya indexes fashion products from many stores and embeds them with a vision-language model. The MCP server lets agents query that index in natural language and reason over the results.\n\n## Tools\n\n| Tool | Description |\n| --- | --- |\n| `discover_products` | Semantic search across all indexed stores. Accepts a natural-language query plus optional filters (category, color, gender, price, etc.) and returns ranked products. |\n| `find_similar_products` | Given a product ID, return visually and semantically similar products. |\n| `discover_brands` | Semantic search over brand profiles. Find brands by style, origin, or aesthetic (e.g. \"Italian streetwear brands\", \"minimalist Scandinavian labels\"). |\n| `find_similar_brands` | Given a brand name or key, return similar brands using brand-profile vectors. |\n| `get_product` | Fetch full details for a single product by ID. |\n| `get_filters` | List available filter values (categories, colors, materials, brands, …) so the agent knows what's filterable. |\n\n## Manual install\n\n### Claude Desktop / Claude Code\n\nAdd to `claude_desktop_config.json` (or your Claude Code MCP config):\n\n```json\n{\n  \"mcpServers\": {\n    \"vistoya\": {\n      \"url\": \"https://api.vistoya.com/mcp\"\n    }\n  }\n}\n```\n\n### Cursor\n\nAdd to `~/.cursor/mcp.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"vistoya\": {\n      \"url\": \"https://api.vistoya.com/mcp\"\n    }\n  }\n}\n```\n\n### VS Code (MCP extension)\n\nAdd to your `mcp.json`:\n\n```json\n{\n  \"servers\": {\n    \"vistoya\": {\n      \"type\": \"http\",\n      \"url\": \"https://api.vistoya.com/mcp\"\n    }\n  }\n}\n```\n\n### Generic stdio fallback (clients that don't support remote yet)\n\nUse [`mcp-remote`](https://www.npmjs.com/package/mcp-remote) as a bridge:\n\n```json\n{\n  \"mcpServers\": {\n    \"vistoya\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"mcp-remote\", \"https://api.vistoya.com/mcp\"]\n    }\n  }\n}\n```\n\n## Example prompts\n\nOnce connected, try:\n\n- \"Find me a black leather jacket under $300\"\n- \"Show me something similar to this product\"\n- \"What cozy sweaters do you have for fall?\"\n- \"Find me running shorts under $100\"\n\n## Discoverability\n\nThis server is published on the official MCP Registry. You can find it at:\n\n```\nhttps://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.vistoya/market\n```\n\n## Status\n\nPublic preview. The endpoint is publicly reachable and does not currently require authentication.\n\n## License\n\nMIT — see [LICENSE](./LICENSE).\n\n## Contact\n\nIssues and feature requests: open an issue on this repo.\n",
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