Fragrance & Perfume MCP (Noteboxd)

perfumer_get

Read-onlyIdempotent

Get a perfumer's profile (bio, country, house affiliation) and their top fragrances by community score.

See also: fragrance_search to find more fragrances by this perfumer · brand_get if you want the brand they work for.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>",
      "context": "<context>"
    },
    "name": "perfumer_get"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	Yes	Perfumer slug, e.g. 'francis-kurkdjian', 'jacques-polge'
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`response_format`	No		markdown

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 27, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "slug"
-]New value: +[
+  "slug",
+  "context"
+]

Changed3 schema fields changedOct 17, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

removedInput schema / properties / context

Removed value: -{
-  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
-  "type": "string"
-}

changedInput schema / required

Previous value: -[
-  "slug",
-  "context"
-]New value: +[
+  "slug"
+]

First observedOct 1, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, open-world, non-destructive behavior, so the description's job is to add content context — which it does by naming the profile fields and the ranking basis ('community score'). It does not say how many top fragrances are returned, how ties/missing scores are handled, or what happens with an unknown slug.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core operation, followed by a compact routing line. Zero filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must convey return shape — it lists the profile fields and the top-fragrance bundle, which is adequate. Gaps are minor: count of top fragrances, pagination, and error behavior for an invalid slug are unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%: slug carries examples ('francis-kurkdjian'), context is fully documented, and response_format has an enum plus default. The description adds nothing about any parameter, so it neither compensates nor detracts — baseline 3 for moderate coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get a perfumer's profile') and enumerates the returned fields (bio, country, house affiliation, top fragrances by community score). Clearly distinct from siblings like brand_get and fragrance_get.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'See also' line routes the agent to two concrete alternatives with the conditions that select them: fragrance_search for more fragrances by the perfumer, brand_get for the brand they work for. It stops short of stating when not to use this tool (e.g., for a single fragrance, use fragrance_get).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Fragrance & Perfume MCP (Noteboxd) tools Inspect

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