scentrev-mcp

npx add-mcp 'https://api.scentrev.com/mcp/'

Perfume MCP docs

22 perfume MCP tools that turn community fragrance knowledge into clean, structured data. Ask in plain English - your agent handles the rest.

You ask · your agent calls the API

“Best beast-mode winter scent from Lattafa?”

No SQL, no slugs to memorize. Ask in plain English. Each tool below includes copy-ready examples for that exact use case.

Try tools live in the Playground

Signed-in users can run any of the 22 MCP tools from the dashboard — no Cursor or Claude required. Guests can browse recipe prompts and sign in to try live.

Category cheat sheet

Exact filter labels for search_fragrances_filtered and blend tools: longevity, sillage, rating, appreciation, discovery sort, and more.

Open scoring & categories

01

Generate a key

Sign in with Google, GitHub, or email, then create a key on the API Keys page. One active key per account.

02

Add the config

Paste the OAuth block (URL only) into Cursor, Claude, or VS Code and approve the browser prompt. Or paste a bearer key. REST calls use the key.

03

Ask away

Type a question in plain English. Your agent picks the right tool and returns structured longevity, sillage, notes, and sentiment data.

What you can ask

Three common flows. Pick a tool in the sidebar for more examples tied to that endpoint.

Discover

search_fragrances → search_fragrances_filtered

• “Find Creed Aventus.”
• “Best summer office scents with moderate sillage.”
• “Hidden gems from Lattafa with strong longevity.”

Analyze one scent

get_fragrance_profile · get_performance · get_appreciation

• “Full profile for Creed Aventus.”
• “Is Layton loud or intimate?”
• “Do people love Club de Nuit Intense?”

Compare & blend

get_reminds_of · search_by_references

• “What smells like Aventus but cheaper?”
• “Blend Aventus with Oud Wood.”
• “Alternatives to Lost Cherry.”

Connect with OAuth

Point the client at https://api.scentrev.com/mcp/ with no API key. It opens the consent page, you sign in, and the client stores a token.

Cursor, Claude Desktop, and VS Code can sign in through OAuth. Use this when you do not want to paste a frag_live_ key. REST calls still need an API key.

1. 1Add the server with only the URL. Do not paste an API key.
2. 2Save and reload the client. It opens a browser window to sign in.
3. 3Sign in with Google, GitHub, or email, then choose Allow.
4. 4The fragrance tools appear in the client. Revoke them later under Settings.

Cursor / Claude / VS Code

{
  "mcpServers": {
    "scentrev-mcp": {
      "url": "https://api.scentrev.com/mcp/"
    }
  }
}

After you allow access, the app is listed in Settings → Connected apps.

Or connect with an API key

The same bearer key works for MCP and for direct REST calls at https://api.scentrev.com.

Cursor / Claude Desktop · mcp.json

{
  "mcpServers": {
    "scentrev-mcp": {
      "url": "https://api.scentrev.com/mcp/",
      "headers": {
        "Authorization": "Bearer frag_live_YOUR_KEY"
      }
    }
  }
}

Generate the key from the dashboard after signing in. Creating a new key revokes the previous one.

Install on Smithery

Connect through Smithery with your API key. Same upstream endpoint and tools as a direct MCP client config.

Listed on PeerPush

Find scentrev-mcp on PeerPush and leave a rating if the perfume MCP is useful in your stack.

Output rules

Four invariants every response follows, so you can trust the shape of the data you build on.

Ratios only

Raw likes, dislikes, vote JSON, and 0-5 star averages are never exposed. You get normalized scores instead. Star rating is out of 5 - convert with score × 5, never × 10.

n_records, not confidence

Every metric carries n_records - how many community votes shaped it. Over 500 is a strong signal; under 100 is thin data.

0-1 everywhere

All wear metrics are normalized to 0-1 with a category label. The one exception: accord percentages run 0-100.

Rating vs reviews

Star rating uses n_records (rating votes) on a 0-5 scale. reviews_count is how many written text reviews exist - a separate number, not a /5 or /10 score.

A typical metric object

Score, category, vote count, and how to read the axis - every time.

{
  "score": 0.62,
  "category": "moderate",
  "n_records": 1240,
  "scale": "0 = X, 1 = Y"
}

Ready to build? Get your API key