Fragrance MCP · Perfume MCP · 126k+ scents
Perfume MCP with a sense of smell
Free fragrance MCP and perfume MCP server for AI agents. Query 126k+ scents for longevity, sillage, seasonality, and community scores from Cursor or Claude.
Full profile for Creed Aventus
Aventus
Creed · 8,420 wear votes
long lasting · high confidence
strong · high confidence
beloved · high confidence
Depth you can actually query
Every filter and recommendation draws on structured notes, accords, perfumers, and community similarity. Real signals, not vibes.
0k+
Fragrances
0+
Brands
0+
Perfumers
0
Notes
0+
Accords
0
MCP tools
Built in India
India's first MCP for perfume data
ScentRev MCP is the first Model Context Protocol server in India dedicated to structured fragrance intelligence: longevity, sillage, seasonality, accords, and community scores your agents can query in one call. Read the perfume MCP guide to install it in Cursor or Claude.
- 126k+ fragrances, normalized for LLMs and REST
- Drop into Cursor, Claude Desktop, or your own stack
- Free during the current period. No credit card
Drops into any MCP client
One call, the whole story of a scent
Community knowledge, normalized into metrics your agents and apps can trust.
Full fragrance profiles
Longevity, sillage, seasonality, gender lean, sentiment, accords, and similar fragrances. One structured response, no scraping.
MCP-native
Drop into Cursor or Claude Desktop with one config block.
Normalized scores
Every metric is 0 to 1 with an n_records confidence count. No raw vote dumps.
REST or MCP, same scoring model
Call it from an agent or hit the endpoints directly. You get the same normalized data either way.
- Bearer-key auth, no OAuth dance
- Predictable JSON, typed fields
- Confidence counts on every metric
{
"mcpServers": {
"scentrev-mcp": {
"url": "https://api.scentrev.com/mcp/",
"headers": {
"Authorization": "Bearer frag_live_..."
}
}
}
}Ask in plain language, get structured data back
14 tools, one fragrance brain
Search, filter, and pull structured profiles from community data.
search_fragrances
Free-text search across the catalog
search_fragrances_filtered
Filter by brand, season, notes, discovery sort
search_by_references
Blend note pyramids from 2+ reference scents
list_brands
Browse brands with fragrance counts
resolve_slug
Resolve informal names to slugs
compare_fragrances
Side-by-side wear and value metrics
get_fragrance_profile
Every metric for one fragrance
get_wear_summary
When and where it shines
get_identity
Gender lean and character
get_performance
Longevity and sillage scores
get_appreciation
Community sentiment and love score
get_reminds_of
Closest-smelling alternatives
get_note_pyramid
Top, heart, and base notes
get_accords
Dominant accords, weighted
Connected in under a minute
Create a key
Sign up and generate a key in the dashboard. No credit card.
Add the config
Paste one block into Cursor or Claude Desktop. That is the whole setup.
Ask your agent
Your agent now answers fragrance questions with structured, sourced data.
Questions, answered
Everything you need to know before wiring scentrev-mcp into your stack. Still stuck? The docs go deeper.
Start building in minutes
Sign up, generate a key, connect your MCP client. No credit card, no quotas.