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lzinga

US Government Open Data MCP

by lzinga

fda_device_enforcement

Read-onlyIdempotent

Search FDA device recall enforcement reports by recall class, date range, or company to identify dangerous medical device recalls.

Instructions

Search FDA device recall enforcement reports. Same classification system as drug/food recalls: Class I (most dangerous) to Class III. Note: Records before June 2012 may lack some fields.

Example searches:

  • 'classification:"Class I"' — most dangerous recalls

  • 'report_date:[20200101+TO+20231231]' — recalls in date range

  • 'recalling_firm:"Medtronic"' — by company

Count fields: voluntary_mandated.exact, classification.exact, status.exact

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 10, max 100)
searchNoOpenFDA search query. Examples: 'field:value', 'field:"Exact Phrase"', 'field:[20200101+TO+20231231]', '_exists_:field'. Combine with '+AND+', '+OR+', '+NOT+'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / limit / default
      Added value: +10
  2. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv2026.3.9

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: the classification system (Class I-III), the caveat about records before June 2012 lacking fields, and the count fields available. This goes beyond the annotations.

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 with a clear opening sentence, a useful note about data quality, and concrete examples. It's slightly longer than necessary but every section earns its place by providing actionable query patterns.

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?

For a search tool with 2 parameters and no output schema, the description covers the key aspects: what it searches, how to construct queries, and data caveats. It doesn't describe the return format, but the absence of an output schema and the simplicity of the tool make this acceptable.

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 description coverage is 100%, so the schema already documents both parameters. The description adds value by providing concrete query syntax examples and listing count fields, which helps the agent construct effective searches beyond the schema's generic examples.

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 clearly states the tool searches FDA device recall enforcement reports, with a specific verb ('Search') and resource ('FDA device recall enforcement reports'). It distinguishes itself from sibling tools like fda_device_recalls by focusing on enforcement reports, and the classification system note adds clarity.

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 description provides example searches and count fields, giving clear context on how to use the tool. It doesn't explicitly state when to use this tool versus alternatives like fda_device_recalls, but the examples and classification note imply the usage context well.

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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