Skip to main content
Glama

Deep Research Document

fetch
Read-onlyIdempotent

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
NameRequiredDescriptionDefault
idYesIdentifier of a document returned by `search`

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique identifier of the document on this server; what `fetch` takes
urlYesCanonical public URL of the document — ChatGPT's citation depends on it
textYesFull readable content of the document (Markdown)
titleYesHuman-readable title of the document
metadataNoAdditional key/value pairs about the document (kind, source, period…)
provenanceYesProvenance block (contract v1.1): source, URL, data vintage, extraction instant, origin diagnostics, citation, license
attributionYesCanonical source URLs of this response (attribution list)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedOutput schema / properties / provenance / description
      Previous value: -"Provenance block (contract v1.0): source, URL, data vintage, extraction instant, citation, license"New value: +"Provenance block (contract v1.1): source, URL, data vintage, extraction instant, origin diagnostics, citation, license"
    • addedOutput schema / properties / provenance / properties / retrieval
      Added value: +{
      +  "anyOf": [
      +    {
      +      "additionalProperties": false,
      +      "properties": {
      +        "anomalies": {
      +          "description": "Anomalias superadas até o sucesso, somadas por classe, em ordem fixa; [] se nenhuma",
      +          "items": {
      +            "additionalProperties": false,
      +            "properties": {
      +              "count": {
      +                "description": "Ocorrências desta classe na chamada",
      +                "maximum": 9007199254740991,
      +                "minimum": 1,
      +                "type": "integer"
      +              },
      +              "kind": {
      +                "description": "Classe da anomalia (vocabulário fechado do contrato)",
      +                "enum": [
      +                  "timeout",
      +                  "network",
      +                  "http_4xx",
      +                  "http_5xx",
      +                  "rate_limited",
      +                  "malformed_body"
      +                ],
      +                "type": "string"
      +              }
      +            },
      +            "required": [
      +              "kind",
      +              "count"
      +            ],
      +            "type": "object"
      +          },
      +          "type": "array"
      +        },
      +        "attempts": {
      +          "description": "Tentativas somadas, incluindo as repetidas (>= requests)",
      +          "maximum": 9007199254740991,
      +          "minimum": 1,
      +          "type": "integer"
      +        },
      +        "requests": {
      +          "description": "Idas distintas à origem que compõem esta resposta (fatias, páginas)",
      +          "maximum": 9007199254740991,
      +          "minimum": 1,
      +          "type": "integer"
      +        },
      +        "unstable": {
      +          "description": "true se houve repetição (attempts > requests) ou alguma anomalia",
      +          "type": "boolean"
      +        }
      +      },
      +      "required": [
      +        "requests",
      +        "attempts",
      +        "anomalies",
      +        "unstable"
      +      ],
      +      "type": "object"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "description": "Origin diagnostics of THIS source in this call (contract v1.1): requests made to the upstream, attempts summed across retries, anomalies worked around (kind + count); unstable=true when any anomaly happened. null when nothing was measured (bundled dataset, or response served entirely from cache)"
      +}
    • changedOutput schema / properties / provenance / required
      Previous value: -[
      -  "source",
      -  "source_url",
      -  "data_vintage",
      -  "retrieved_at",
      -  "citation",
      -  "license"
      -]New value: +[
      +  "source",
      +  "source_url",
      +  "data_vintage",
      +  "retrieved_at",
      +  "retrieval",
      +  "citation",
      +  "license"
      +]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/open-world, so the safety profile is covered. The description still adds real context beyond them: an unknown id returns an error, and the fetch is a live GET against the public source rather than a cache hit. That error and live-fetch disclosure is valuable, though it does not cover rate limits or pagination.

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?

Front-loads what it returns before explaining context, and each block (return shape, contract/catalog scope, id validity, sibling routing, behavior) earns its place. Slightly long with three paragraphs for a one-parameter tool, but no filler.

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?

With an output schema present, return values are already structured, yet the description still summarizes the payload and adds error behavior, catalog scope, and routing to sibling tools. An agent has everything needed to call this correctly in the Deep Research contract.

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

Parameters4/5

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

Schema coverage is 100% and the schema already describes the single `id` parameter as coming from `search`, so baseline is 3. The description adds the consequential constraint that only ids from `search` are valid and that an unknown id produces an error, which meaningfully augments the parameter's semantics.

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 ('Returns the full document for an id obtained from `search`') and specifies the exact return shape ('{ id, title, text, url, metadata }'). It names its sibling `search` as the source of the id, so an agent can instantly distinguish fetch (retrieve full doc) from search (find ids).

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?

Explicitly states the prerequisite that only ids returned by `search` are valid and that unknown ids error, and it names the alternative set — the `*_*` terminology tools plus `find_equivalent`/`validate_codes` — as the tools for actual data queries. This is 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.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.