FDA Data MCP

Facility Detail

fda_get_facility

Read-onlyIdempotent

Detailed facility profile by FEI number. Returns: facility name, full address, operations type (Manufacture, API, Repack, Contract Manufacture, etc.), establishment types (Manufacturer, Distributor, Specification Developer, etc.), registrant and owner/operator info, DUNS number, registration expiry, enforcement history (recalls), device products with classification, and a facility_risk_summary (inspection counts by classification, warning letters, last inspection date). Requires: FEI number — get it from fda_search_facilities or fda_company_full. Excludes: full inspection details and citations. Related: fda_inspections (inspection history by FEI), fda_citations (CFR violations by FEI), fda_compliance_actions (warning letters/seizures by FEI), fda_import_refusals (import refusal history by FEI), fda_facility_products (paginate large product lists).

Input Schema

TableJSON Schema

Name	Required	Description
`fei`	Yes	FDA Establishment Identifier (FEI number)
`products_limit`	No	Products result limit
`products_offset`	No	Products result offset

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safe read-only nature is known. The description goes beyond by detailing the exact fields returned, the exclusions, and the relationships to other tools, providing a clear behavioral contract without contradiction.

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 long but highly structured: returns, requires, excludes, related tools. Every sentence carries meaningful information for a complex tool. It is more comprehensive than concise, but its length is justified by the tool's complexity.

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 absence of an output schema, the description thoroughly covers return fields, prerequisites, exclusions, and sibling alternatives. It provides a complete picture of when and how to invoke the tool, making it self-sufficient for an agent.

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?

All three parameters have descriptive entries in the schema (FEI pattern, numeric limits for products_offset/limit). The description mentions the FEI requirement and suggests sources, adding slight context, but does not significantly enhance the schema's parameter documentation. Baseline of 3 applies due to 100% schema coverage.

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 it provides a detailed facility profile by FEI number, enumerating the specific data returned. It distinguishes itself from sibling tools by listing exclusions and related tools for other use cases (e.g., fda_inspections for inspection details).

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 required input (FEI number) and where to obtain it (fda_search_facilities or fda_company_full). Also specifies what is excluded and names alternative tools for those needs (inspections, citations, compliance actions, import refusals, facility products).

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

All FDA Data MCP tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0

Disambiguation4/5

Most tools have distinct purposes with clear boundaries, such as fda_search_drugs for drug applications and fda_search_510k for device clearances. However, some overlap exists, like fda_device_udi and fda_device_udi_lookup both querying UDI data, which could cause confusion despite differences in scope.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a clear fda_ prefix, using descriptive verbs like search, get, list, and link. This uniformity makes the set predictable and easy to navigate, with no deviations in naming style.

Tool Count2/5

With 48 tools, the count is excessive for a single server, making it overwhelming and difficult for agents to manage. While the domain is broad (FDA data), the toolset feels bloated with many specialized or overlapping tools that could be consolidated.

Completeness5/5

The toolset provides comprehensive coverage of FDA data domains, including drugs, devices, inspections, compliance, recalls, and facilities. It supports full CRUD-like operations (e.g., search, get, link, save) and lifecycle workflows, with no obvious gaps for the intended purpose.

Resources

Need Help?