Medical Terminologies MCP

Deep Research Document

fetch

Read-onlyIdempotent

Retrieve the full document text and canonical citation URL for any ID returned by search, giving direct access to readable content and the public source page.

Instructions

Returns the full document for an id obtained from search, as { id, title, text, url, metadata }: text is the readable content (Markdown) and url the canonical public page to cite.

Companion of search in the OpenAI Deep Research contract, over the medical terminologies (CID-10 categories and chapters, ICD-11, LOINC, RxNorm, MeSH, terminology version records) catalog. Only ids returned by search are valid; an unknown id returns an error. The terminology tools (icd11_*, cid10_*, loinc_*, rxnorm_*, mesh_*, atc_*, map_*, find_equivalent, validate_codes) remain the tools for data queries.

Behavior: read-only and idempotent — a live GET against the public source when the document needs it.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Identifier of a document returned by `search`

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Unique identifier of the document on this server; what `fetch` takes
`url`	Yes	Canonical public URL of the document — ChatGPT's citation depends on it
`text`	Yes	Full readable content of the document (Markdown)
`title`	Yes	Human-readable title of the document
`metadata`	No	Additional key/value pairs about the document (kind, source, period…)
`provenance`	Yes	Provenance block (contract v1.0): source, URL, data vintage, extraction instant, citation, license
`attribution`	Yes	Canonical source URLs of this response (attribution list)

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.11.0Sep 15, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive hints. The description adds useful behavioral context: unknown ids return an error, the operation is a live GET against the public source when needed, and the return payload has a defined shape. This goes beyond annotation-only information.

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

Conciseness4/5

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

The description is well-structured and front-loads the return contract, then context, then behavior. It is a bit longer than strictly necessary because it restates some annotation-backed properties, but every paragraph adds useful orientation.

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 one-parameter tool with a rich output schema and complete annotations, the description covers return shape, valid input source, error behavior, positioning relative to siblings, and safety semantics. Nothing critical is missing for an agent to select and invoke it correctly.

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?

The input schema already describes `id` as 'Identifier of a document returned by `search`' at 100% coverage. The description reinforces this by explaining the id must come from `search`, but it does not add new format or syntax details. With full schema coverage, the baseline 3 is appropriate.

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 uses a specific verb ('Returns') with a clear resource (the full document for an id from `search`) and specifies the exact output shape. It also separates itself from the terminology data-query tools, so an agent can distinguish it from siblings without ambiguity.

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

Usage Guidelines5/5

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

It explicitly states that `fetch` is the companion of `search`, that only ids returned by `search` are valid, and that terminology tools should be used for data queries instead. This gives clear when-to-use and when-not-to-use guidance.

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