FDA Data MCP

Substance Lookup

fda_substance_lookup

Read-onlyIdempotent

Look up FDA substance data by UNII code (exact match) or substance name (fuzzy match). Returns substance name, UNII, substance class, molecular formula, and related details. Use to identify active pharmaceutical ingredients.

Input Schema

TableJSON Schema

Name	Required	Description
`unii`	No	UNII code (exact match)
`limit`	No	Max results to return (1-500)
`offset`	No	Result offset for pagination
`substance_name`	No	Substance name (fuzzy match)

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. Description adds behavioral details about exact vs fuzzy matching and the specific return fields (substance name, UNII, class, formula). It does not mention pagination behavior, but schema covers limit/offset.

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

Conciseness5/5

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

Two concise sentences, front-loaded with the primary purpose, no redundancy with schema or annotations.

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 simple lookup with rich annotations and fully documented parameters, the description covers the use case, match types, and return fields. Minor gap: 'related details' is vague, and there is no output schema, but this is acceptable for this tool.

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 4 parameters have schema descriptions (100% coverage), so baseline is 3. Description reinforces the exact/fuzzy distinction already present in the schema but adds no new syntax or format details for parameters.

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?

Description uses specific verb 'look up' + resource 'FDA substance data', specifies exact vs fuzzy matching, and distinguishes from sibling tools by referencing UNII code. It also states the intended use case ('identify active pharmaceutical ingredients').

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?

Provides a clear use case ('Use to identify active pharmaceutical ingredients') and specifies lookup by UNII or name. However, it doesn't explicitly contrast with alternative FDA lookup tools or state when not to use this tool.

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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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

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