Govparse Government Data Gateway

firmstanding_company_search

Which employers appear in federal enforcement and compliance records? Search 3.7M resolved employer entities by name (suffix/punctuation-insensitive, trigram-indexed), state, linked source (whd, osha, echo, oflc, fmcsa, leie, sam_exclusions), NAICS prefix, or source-count range. Returns entity IDs for the business360 dossier plus identity, address, and source/record counts. total_matched caps at 1000 — narrow when capped. Not a consumer report; no FCRA use. [price: $0.05/row]

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	Company name fragment — normalized before matching ('Swift Transportation Co. of Arizona, LLC' → 'SWIFT TRANSPORTATION'). Example: 'swift transportation'.
`sort`	No	field:direction — source_count \| record_count \| last_seen. Default 'source_count:desc'.
`limit`	No	Max rows (default 25, cap 100).
`naics`	No	NAICS code prefix(es), CSV. Example: '3116' covers animal processing.
`state`	No	Entity state code(s), CSV. Example: 'AZ'.
`offset`	No	Rows to skip, for paging.
`source`	No	Only entities with linked records in these sources (CSV): whd \| osha \| echo \| oflc \| fmcsa \| leie \| sam_exclusions.
`source_count_max`	No	Maximum number of distinct federal sources the entity appears in.
`source_count_min`	No	Minimum number of distinct federal sources the entity appears in (1-7).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedJul 24, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description takes on full burden. It discloses name matching behavior (suffix/punctuation-insensitive, trigram-indexed), the 1000 cap, and that it is not a consumer report (no FCRA use). Pricing is also noted. Missing details on timeout or exact response structure, but overall informative.

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?

The description is concise (4 sentences), front-loaded with the purpose, and each sentence adds essential information: purpose, matching details, output, cap warning, and pricing. No redundant or missing parts.

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?

Given no output schema, the description sufficiently describes return fields (entity IDs, identity, address, source/record counts). It also covers the cap and pricing. Could be more complete with pagination behavior or data recency, but it is adequate for an agent to use correctly.

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 coverage is 100% with descriptions and examples for all 9 parameters. The description adds context beyond the schema, such as the matching normalization and the meaning of 'source'. This helps an agent select correct values.

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 opens with a clear question and states it searches 3.7M employer entities by name and various filters. It specifies the resource (federal enforcement and compliance records) and the action (search), distinguishing it from sibling tools like firmstanding_business360 which retrieves a specific dossier.

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 clear context: what entities are searched, what is returned, and a warning about the 1000 cap. It also notes the pricing model. However, it does not explicitly mention when to use this tool vs. alternatives such as firmstanding_business360_lookup or other search tools, though the purpose is distinct enough.

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

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct domain and specific action (e.g., FDA approvals vs clearances vs recalls; firmstanding business360 dossier vs search vs screen). Even overlapping concepts like 'business360' vs 'business360_lookup' are distinguished by input (UUID vs name+state). No two tools appear to do the same thing.

Naming Consistency5/5

All tools use a consistent lowercase snake_case pattern with domain prefix (e.g., fda_*, firmstanding_*, fmcsa_*, govcon_*). Action words (search, lookup, screen, feed, stats) follow predictable usage. The naming is uniform and easy to parse.

Tool Count4/5

38 tools is on the higher end but appropriate for a comprehensive government data gateway spanning multiple agencies and datasets. Each domain has a reasonable number of tools (e.g., FMCSA: 7, OFLC: 6). Could potentially be trimmed slightly, but overall well-scoped for the stated purpose.

Completeness5/5

The tool surface covers the major government data sources comprehensively: FDA (approvals, clearances, recalls), FMCSA (carrier census, safety, insurance, etc.), FSIS, DOJ/OFLC, OSHA/EPA/DOL enforcement, SEC insider filings, clinical trials, VA facilities/opportunities/vendors, and federal contracting. No obvious gaps for the stated gateway purpose.

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