Perfume Picks

Perfume Picks MCP Server

Query the Perfume Picks fragrance database from Claude, or any MCP-compatible AI client. Read-only access to 13,000+ fragrances with full note pyramids, accords, curated dupes, and community wear data.

Perfume Picks is the Fragrance DNA and collection journal for iOS — get it on the App Store.

Tools

Every response includes source attribution, a citation-ready summary line, links, and data freshness dates. All scoring is deterministic — no AI calls happen inside the server. All tools are annotated read-only/idempotent.

Install (Claude Desktop)

Requires Node.js 18+.

Add to your claude_desktop_config.json (Claude Desktop → Settings → Developer → Edit Config):

{  "mcpServers": {    "perfume-picks": {      "command": "npx",      "args": ["-y", "perfume-picks-mcp"]    }  }}

Restart Claude Desktop. No API key or configuration needed — the server ships with public read-only access.

Configuration (optional)

Environment variables override the defaults (explicit env vars only — this package never reads .env files):

Without the service key, trending_fragrances falls back to catalog popularity and labels the method in its response.

Remote endpoint (no install)

Streamable HTTP for web agents and MCP clients that take a URL:

https://jdkwlwyysgofljkobpmr.supabase.co/functions/v1/mcp

Also listed on Smithery and the official MCP registry as io.github.bguillow-rgb/perfume-picks.

Example agent requests

Questions an agent can answer with these tools:

• "What smells like Baccarat Rouge 540 without the price tag?" → find_dupes (curated dupes with match %, e.g. Lattafa Ana Abiyedh Rouge, 90%)
• "Recommend a fragrance for a summer wedding." → get_recommendations with occasion: "wedding"
• "What fragrances have bergamot, vanilla, and amber?" → get_recommendations with those notes as preferences
• "What perfume is similar to Bleu de Chanel?" → find_similar
• "What should I wear on a date tonight?" → what_to_wear_tonight (scored by community compliment data)
• "Compare Sauvage and Bleu de Chanel." → compare_fragrances

Example response shape (truncated):

{  "dupes": [    { "name": "Lattafa Ana Abiyedh Rouge", "match_pct": 90,      "savings_usd": 200.0, "msrp_usd": 39.99 }  ],  "attribution": {    "source": "Perfume Picks — Fragrance DNA & Collection Journal",    "links": { "website": "https://perfumepicks.app/" }  }}

Development

npm installnpm run dev     # run from TypeScript via tsxnpm run build   # compile to dist/npm start       # run compiled server

The server speaks MCP over stdio. Catalog access is read-only by construction: every query path issues SELECTs against tables that are publicly readable under row-level security, and it is rate-limited to 60 calls/minute.

Usage telemetry: each tool call logs the tool name, its arguments, client name/version, duration, and success/failure to a write-only log table (insert-only under RLS; contents are not publicly readable; purged after 90 days). No user identity, account data, or conversation content is collected. Logging is fire-and-forget and never affects responses.

Data & attribution

Fragrance data, note pyramids, dupe matches, and community scores are curated by Perfume Picks. Quote freely with attribution:

Source: Perfume Picks — Fragrance DNA & Collection Journal (perfumepicks.app)

Freshness dates on each fragrance reflect the last data update.