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MeSH Descriptor Details

mesh_descriptor
Read-onlyIdempotent

Retrieve complete MeSH descriptor details by ID, including scope notes, tree numbers, related concepts, synonyms, and official translations in 10 languages.

Instructions

Get detailed information about a MeSH descriptor by ID.

Use this tool to:

  • Get the full definition (scope note) of a MeSH term

  • View tree numbers showing hierarchy location

  • See related concepts and synonyms

Provide a MeSH Descriptor ID like "D015242" (Ofloxacin). Set language to request NLM's official translations where they exist (e.g. language: "pt").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mesh_idYesMeSH Descriptor ID (e.g., D015242, D003920)
languageNoLanguage code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.en

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
uriYes
labelYes
conceptsYes
provenanceYesProvenance block (contract v1.0): source, URL, data vintage, extraction instant, citation, license
qualifiersYes
scope_noteYes
attributionYesCanonical source URLs of this response (attribution list)
tree_numbersYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.9.1
    • removedOutput schema / properties / provenance / properties / data_vintage / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedOutput schema / properties / provenance / properties / data_vintage / type
      Added value: +[
      +  "string",
      +  "null"
      +]
    • removedOutput schema / properties / provenance / properties / license / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedOutput schema / properties / provenance / properties / license / type
      Added value: +[
      +  "string",
      +  "null"
      +]
  2. Changed4 schema fields changedv1.8.0
    • changedInput schema / properties / language / description
      Previous value: -"Language code (default: en)"New value: +"Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated."
    • addedOutput schema / properties / attribution
      Added value: +{
      +  "description": "Canonical source URLs of this response (attribution list)",
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • addedOutput schema / properties / provenance
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "Provenance block (contract v1.0): source, URL, data vintage, extraction instant, citation, license",
      +  "properties": {
      +    "citation": {
      +      "description": "Ready-to-use citation/attribution string",
      +      "type": "string"
      +    },
      +    "data_vintage": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ],
      +      "description": "Version/release of the data as exposed by the source; null when not exposed"
      +    },
      +    "license": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ],
      +      "description": "License / legal regime of the data"
      +    },
      +    "retrieved_at": {
      +      "description": "Real instant of the upstream extraction (ISO-8601, UTC). Responses served from cache keep the ORIGINAL fetch instant.",
      +      "type": "string"
      +    },
      +    "source": {
      +      "description": "Official upstream source of this data",
      +      "type": "string"
      +    },
      +    "source_url": {
      +      "description": "Canonical URL of the source (API base or dataset release)",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "source",
      +    "source_url",
      +    "data_vintage",
      +    "retrieved_at",
      +    "citation",
      +    "license"
      +  ],
      +  "type": "object"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "id",
      -  "uri",
      -  "label",
      -  "scope_note",
      -  "tree_numbers",
      -  "concepts",
      -  "qualifiers"
      -]New value: +[
      +  "id",
      +  "uri",
      +  "label",
      +  "scope_note",
      +  "tree_numbers",
      +  "concepts",
      +  "qualifiers",
      +  "provenance",
      +  "attribution"
      +]
  3. Changed1 schema field changedv1.5.7
    • removedInput schema / additionalProperties
      Removed value: -false
  4. Changed1 schema field changedv1.4.0
    • addedInput schema / properties / language
      Added value: +{
      +  "default": "en",
      +  "description": "Language code (default: en)",
      +  "enum": [
      +    "en",
      +    "es",
      +    "pt",
      +    "fr",
      +    "de",
      +    "it",
      +    "zh",
      +    "ja",
      +    "ar",
      +    "ru"
      +  ],
      +  "type": "string"
      +}
  5. First observedv1.2.1

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to restate those. It adds useful behavioral context by noting that language enables NLM's official translations only where they exist, and it lists the kind of data returned. This goes beyond the annotations without contradicting them.

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?

The description is compact and front-loaded: the main action comes first, followed by a tight bullet list and a practical example. Every sentence earns its place, and there is no filler or redundant restating of the tool title.

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

Completeness5/5

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

For a simple read-only lookup with two parameters, an output schema, and strong annotations, the description covers everything an agent needs: the lookup key, the optional language behavior, and the kind of information returned. Nothing critical is missing.

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 description coverage is 100%, so the baseline is 3. The description reinforces the mesh_id example and language usage, but it does not add substantial meaning beyond what the schema already documents. It is adequate but not additive.

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?

The description opens with a specific verb and resource: 'Get detailed information about a MeSH descriptor by ID.' It then lists concrete outputs (scope note, tree numbers, concepts, synonyms), and the 'by ID' framing clearly separates it from search-style siblings like mesh_search and mesh_tree.

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 'Use this tool to:' section gives explicit, actionable use cases for when the tool is appropriate. It does not mention alternative tools or when not to use it, but the intended usage context is clear enough for an agent to select it correctly.

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