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mcp-sam-gov

by cliwant

openfda_device_clearances

Read-only

Search and filter FDA 510(k) premarket-notification clearances for medical devices by applicant, device name, clearance number, and more.

Instructions

Search openFDA 510(k) DEVICE CLEARANCES — the FDA's premarket-notification (510(k)) clearances for medical devices, with the applicant/manufacturer, device name, clearance number (K-number), decision (date + description), clearance type, product code, advisory committee, and geography (openFDA /device/510k.json; api.fda.gov). KEYLESS (an OPTIONAL free OPENFDA_API_KEY only RAISES the rate limit — keyless works at ~1000 requests/day; it NEVER throws for a missing key; get one at https://open.fda.gov/apis/authentication/; call api_key_status to see every source's key requirement). Input: STRUCTURED filters — applicant (→applicant), deviceName (→device_name), productCode (→product_code), clearanceType (→clearance_type, e.g. Traditional/Special/Abbreviated), kNumber (→k_number, e.g. 'K123456'), state (2-letter, e.g. 'CA') — the tool safely assembles + escapes these into the openFDA search= Lucene string (NO raw passthrough — injection-safe), plus limit (1..100, default 25) and skip (offset ≥0). Returns { clearances:[{ applicant, deviceName, kNumber, decisionDate, decisionDescription, clearanceType, productCode, advisoryCommittee, state }] } + honest _meta. HONESTY: totalAvailable is openFDA's EXACT meta.results.total (skip/limit pagination via hasMore/nextOffset — never results.length); every scalar (dates included, decision_date is a YYYY-MM-DD string) is null-never-empty-string. ★A no-match query returns openFDA HTTP 404 NOT_FOUND ⇒ an HONEST EMPTY (returned:0, totalAvailable:0), NOT an error; a 400 syntax error ⇒ invalid_input surfacing openFDA's message; a 5xx ⇒ THROWS; a 200 non-JSON ⇒ schema_drift. The optional key rides ONLY the &api_key= query param — never logged or echoed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoRow offset for pagination (default 0). Page with _meta.pagination.nextOffset.
limitNoMax clearance records to return (default 25, max 100). Offset-paginated via skip.
stateNo2-letter US state/territory postal code filter (→ state), e.g. 'CA'. Validated ^[A-Za-z]{2}$.
kNumberNo510(k) clearance number (K-number) filter (→ k_number), e.g. 'K123456'. Matched as an escaped Lucene phrase.
applicantNoApplicant / manufacturer name filter (→ applicant), e.g. 'medtronic'. Matched as an escaped Lucene phrase.
deviceNameNoDevice name filter (→ device_name), e.g. 'catheter'. Matched as an escaped Lucene phrase.
productCodeNoFDA product code filter (→ product_code), e.g. 'DXN'. Matched as an escaped Lucene phrase.
clearanceTypeNo510(k) clearance type filter (→ clearance_type), e.g. 'Traditional', 'Special', 'Abbreviated'. Matched as an escaped Lucene phrase.
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds extensive behavioral details: honesty policy (nulls never empty strings), error handling (404 returns empty, 400 returns invalid_input, 5xx throws, 200 non-JSON schema_drift), pagination (skip/limit, nextOffset), auth (optional key explanation, rate limits), and injection safety. No contradiction with annotations.

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

Conciseness3/5

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

The description is comprehensive but lengthy, with multiple paragraphs and details about error handling and auth that could be more succinct. While well-structured and front-loaded, it could be trimmed by about 30% without losing essential information.

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?

Given the complexity (8 parameters, no output schema), the description fully explains all filter parameters, return format (listing exact field names), pagination, error handling, and auth. It leaves no gaps in understanding how to invoke and interpret results.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant meaning beyond the schema: it explains the mapping from parameter names to openFDA field names (e.g., deviceName → device_name), validation rules (state regex, limit range), and how filters are safely assembled into Lucene search strings. This helps the agent use parameters correctly.

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 explicitly states it searches openFDA 510(k) device clearances, with specific verb 'Search' and resource 'device clearances'. It details the data source and fields returned, making the purpose unmistakable.

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

Usage Guidelines3/5

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

No explicit guidance on when to use this tool versus siblings like openfda_enforcement or openfda_drug_approvals. The description focuses on how to use filters but does not provide decision criteria or exclusions, which leaves the agent without clear alternatives.

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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