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DailyMed MCP by usefulapi

Get full SPL label document (XML)

dailymed_get_label
Read-only

Fetch the complete Structured Product Label for a SETID as HL7 v3 SPL XML — the full FDA-approved labeling: indications, dosage, warnings, boxed warning, adverse reactions, active/inactive ingredients, etc. NOTE: DailyMed serves the full document only as XML (there is no JSON form), so this returns raw XML text. Use dailymed_search_labels first to find the setid. DailyMed v2: GET /spls/{setid}.xml.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
setidYesThe label SETID (UUID) from dailymed_search_labels.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true. The description adds genuinely useful behavioral context beyond that: the response is 'raw XML text' with 'no JSON form,' which materially affects how an agent must handle the output. It also names the underlying endpoint (GET /spls/{setid}.xml).

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-loaded with the action and resource, then content, then the critical XML-only caveat, then the workflow hint. Dense but well-organized. The 'DailyMed v2: GET /spls/{setid}.xml' trailer is arguably redundant given the endpoint context but is not wasteful.

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?

No output schema exists, so the description carries the burden of explaining the return value, which it does fully (raw HL7 v3 SPL XML text, no JSON). Combined with the prerequisite (find setid via search first) and safety annotation, an agent has everything needed to call and interpret this tool 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?

Schema description coverage is 100%, so the setid parameter's meaning and format are already fully documented in the schema. The description reinforces that the setid comes from dailymed_search_labels but adds no syntax or format detail beyond the schema's pattern and description. 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?

States a specific verb (Fetch) and resource (complete Structured Product Label / full FDA-approved labeling), and enumerates the content sections returned. This clearly differentiates it from siblings like dailymed_label_history, dailymed_label_media, and dailymed_label_packaging, which return narrower slices of a label.

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?

Explicitly states the prerequisite workflow: 'Use dailymed_search_labels first to find the setid.' This gives clear context for obtaining the required ID. However, it does not explicitly contrast when to choose this full-label tool versus the narrower label_* siblings, leaving that inference to the agent.

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

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