AI Furniture Hub
Japan-focused MCP server with 15 tools for mm-precision product search across 300+ items and 31 categories. Curated sets, dimension-compatible replacements, AI visibility diagnosis.
AI Furniture & Home Product Hub - MCP Server
15 tools | 355+ curated products | 31 categories | 90+ brands Millimeter-precision search, curated sets, AI visibility diagnosis, OpenAPI 3.1 schema. Built for ChatGPT, Claude, Gemini, Cursor, Perplexity, and any MCP-compatible AI agent.
Discovery & Install
- MCP Registry name:
io.github.ONE8943/ai-furniture-hub - Remote MCP endpoint:
https://ai-furniture-hub.onrender.com/mcp - Well-known discovery:
https://ai-furniture-hub.onrender.com/.well-known/mcp.json - npm package:
ai-furniture-hub
If your MCP client supports registry search, search for io.github.ONE8943/ai-furniture-hub or AI Furniture & Home Product Hub.
If your client supports direct remote MCP, connect it to https://ai-furniture-hub.onrender.com/mcp.
Why This Exists
AI agents need structured, machine-optimized product data to make useful recommendations. This MCP server provides:
- Exact-fit search: "Find a shelf that fits a 425mm gap" returns products with 1mm accuracy
- Complete solutions: One search returns the shelf + matching storage boxes + floor protection + cable organizers
- Curated by experts: Influencer picks, room presets, bundle deals, and budget hack alternatives
- Replacement intelligence: Discontinued product? Get successors ranked by dimension compatibility (fit_score 0-100)
- AI visibility consulting: Diagnose any website's AI discoverability with a single tool call
Quick Start
Option 1: Remote (Cursor / Claude / VS Code / ChatGPT)
Connect directly to the hosted server:
{
"mcpServers": {
"furniture-hub": {
"url": "https://ai-furniture-hub.onrender.com/mcp"
}
}
}
Works in any MCP client that accepts a remote Streamable HTTP URL.
Option 2: npx (local)
npx ai-furniture-hub
Option 3: Clone & Run
git clone https://github.com/ONE8943/ai-furniture-hub.git
cd ai-furniture-hub
npm install
cp .env.example .env # API keys optional - works with mock data
npm start # stdio mode
npm run start:http # HTTP mode at localhost:3000/mcp
Tools (15)
Search & Discovery
| Tool | What It Does |
|---|---|
search_products | Search 300+ products by keyword, dimensions (mm), price, color, category, brand |
get_product_detail | Full specs: inner dimensions, consumables, compatible storage, curations |
search_rakuten_products | Real-time Rakuten Ichiba search (200K+ listings with prices & reviews) |
search_amazon_products | Amazon affiliate search URL generation with auto SearchIndex |
suggest_by_space | "I have a 600x400mm space" -> everything that fits, rotation-aware |
identify_product | Visual description -> product candidates with model numbers |
Coordination & Comparison
| Tool | What It Does |
|---|---|
coordinate_storage | Shelf + storage box set proposals: quantity per tier, total cost |
compare_products | Side-by-side comparison (2-5 products) on price, size, load, reviews |
find_replacement | Discontinued model -> successors + dimension-compatible alternatives with fit_score |
calc_room_layout | Floor-plan rectangle packing with placement coordinates |
get_related_items | Accessory chains: required items, protection, consumables, hack substitutes (depth 1-2) |
Curation & Intelligence
| Tool | What It Does |
|---|---|
get_curated_sets | Bundles, room presets, influencer picks, hack sets. Filter by type/scene/budget |
get_popular_products | Trending products by category with Rakuten data |
list_categories | Browse 31 categories with counts, brands, samples |
diagnose_ai_visibility | AI visibility audit: llms.txt, robots.txt, JSON-LD, OGP, score 0-100 |
Prompt Workflows (3)
| Prompt | Flow |
|---|---|
room_coordinator | Space dimensions -> shelf + boxes + protection with quantities & cost |
moving_checklist | Floor plan type -> room-by-room purchasing checklist with budget |
product_showdown | Two products -> full comparison including accessories & running costs |
Product Categories (31)
| Area | Categories |
|---|---|
| Storage | Shelves, Color boxes, Storage cases, Clothing storage, Steel racks, Closet storage, File storage |
| Furniture | Desks, TV stands, Bookshelves, Dining, Sofas & chairs, Bedding |
| Room-specific | Kitchen, Laundry, Bath, Entrance, Baby safety |
| Hardware | Tension rods, Protection materials, Parts & accessories, Wagons |
| Appliances | Home appliances, Kitchen appliances, Air quality, Smart home |
| Tech & Lifestyle | PC peripherals, Beauty devices, Gadgets, Health & fitness |
| Decor | Curtains & blinds |
Key Features
Cinderella-Fit Search
All dimensions in millimeters - outer AND inner. Find products that fit a specific space with 1mm tolerance. Rotation-aware: automatically checks if swapping width/depth creates a fit.
Related-Item Chains
Every product links to 3-5 related items: required accessories (HEPA filters for air purifiers), protection materials (floor mats for heavy shelves), consumables (vacuum bags), compatible storage boxes.
Curated Sets
- Bundles: "New Life Starter Kit", "Work From Home Set"
- Room Presets: IKEA-style complete room configurations
- Influencer Picks: Real recommendations from YouTubers and magazines
- Hack Sets: Budget alternatives (100-yen substitutes for 1000-yen accessories)
Dimension-Compatible Replacement
Discontinued product? find_replacement returns:
- DB-registered successors
- Dimension-compatible alternatives with
fit_score(0-100) - Live Rakuten search results
AI Visibility Diagnosis (AIO)
diagnose_ai_visibility audits any URL:
- llms.txt presence
- robots.txt AI crawler access
- Structured data (JSON-LD, Schema.org)
- OGP tags
- Cross-border readiness (English metadata, multi-currency)
- Returns score (0-100), grade (A-F), actionable recommendations
Attribution & Analytics
Every API response includes _attribution metadata with a unique attribution_id, enabling:
- Per-call tracking for pay-per-call monetization
- Source detection (Apify, RapidAPI, direct)
- Contribution logging for revenue attribution
API & Integration
OpenAPI 3.1 Schema
Full OpenAPI spec available at /openapi.yaml for RapidAPI and marketplace integration.
AI Discovery Endpoints
| File | URL | Purpose |
|---|---|---|
| llms.txt | /llms.txt | AI agent overview |
| llms-full.txt | /llms-full.txt | Full tool schemas & examples |
| OpenAPI | /openapi.yaml | REST API specification |
| Server Card | /.well-known/mcp/server-card.json | Machine-readable metadata |
| context.md | /context.md | Structured AI context |
| robots.txt | /robots.txt | AI crawler permissions |
MCP Resources
furniture-hub://llms.txt
furniture-hub://llms-full.txt
Architecture
AI Agent (ChatGPT, Claude, Gemini, Cursor, Perplexity, ...)
| MCP (stdio or Streamable HTTP)
v
+-----------------------------------------------------------+
| 15 Tools + 3 Prompts |
+-----------------------------------------------------------+
| 355+ Products | 31 Categories | 90+ Brands |
| Curated Sets: bundles, room presets, influencer picks |
| Compatibility DB: dimension-based fit scoring |
| Attribution: per-request tracking with attribution_id |
+-----------------------------------------------------------+
| Adapters: Rakuten API / Amazon URL / Nitori |
| Affiliate Engine + Gap Detector + Analytics |
+-----------------------------------------------------------+
|
v
/llms.txt /llms-full.txt /openapi.yaml
/context.md /.well-known/mcp/ /robots.txt
Environment Variables
| Variable | Required | Description |
|---|---|---|
DEPLOYMENT_MODE | No | private (default, affiliate ON) or public (affiliate OFF for marketplace) |
MCP_API_KEYS_FREE | No | Comma-separated free-tier API keys for higher rate limits + curated inner dimensions |
MCP_API_KEYS_PRO | No | Comma-separated pro-tier API keys for unlimited access |
INNER_DIMENSIONS_DATA | Render only | Hidden curated inner-dimension DB injected at build time |
AFFILIATE_ID_AMAZON | No | Amazon Associate tag |
AFFILIATE_ID_RAKUTEN | No | Rakuten Affiliate ID |
RAKUTEN_APP_ID | No | Rakuten API Application ID |
RAKUTEN_API_MOCK | No | true (default) for mock data, false for live |
All environment variables are optional. The server works out of the box with mock data.
Deployment
| Platform | URL |
|---|---|
| MCP Registry | io.github.ONE8943/ai-furniture-hub |
| Render | https://ai-furniture-hub.onrender.com/mcp |
| npm | npx ai-furniture-hub |
Testing
npm run test:ci # Vitest
npm run test:all # Full legacy suite
Contributing
Issues and PRs welcome. See GitHub Issues.
License
MIT
Japanese / 日本語
AI Furniture & Home Product Hub は家具・家電・ガジェット等のAIエージェント向けMCPサーバーです。
-
MCP Registry名:
io.github.ONE8943/ai-furniture-hub -
リモート接続URL:
https://ai-furniture-hub.onrender.com/mcp -
well-known:
https://ai-furniture-hub.onrender.com/.well-known/mcp.json -
355+商品、31カテゴリ、90+ブランド のキュレーション済みカタログ
-
mm精度の寸法検索 - 「幅425mmの隙間にぴったり収まる棚」を即座に発見
-
関連アイテムチェーン - 1商品から3-5個の関連商品（必須アクセサリ、保護材、消耗品）
-
キュレーション - バンドル提案、ルームプリセット、インフルエンサーおすすめ、100均代用ハック
-
後継品検索 - 廃番商品から寸法互換の代替品をfit_scoreで提案
-
AI可視性診断（AIO） - Webサイトの「AIからの見え方」を0-100でスコアリング
-
OpenAPI 3.1 - RapidAPI等のマーケットプレイス連携対応
運営
ONE, Inc.
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