Govparse Government Data Gateway

sba_loans_search

Which companies just got SBA growth capital — a 7(a) guaranty or 504/CDC debenture? Search the SBA 7(a) & 504 FOIA loan-approval roster by company, state, project_state, naics (prefix), program (7A/504), amount_min/amount_max, since (approved on/after a date — the funded-to-grow trigger), business_type, franchise, lender/CDC, entity_id. Returns the borrower, address, gross approval amount, approval date/FY, NAICS, funding lender, and entity-resolved borrower. SBA public-domain records. [price: $0.05/row]

Input Schema

TableJSON Schema

Name	Required	Description
`sort`	No	approval_date \| amount \| company \| jobs :asc\|:desc. Default approval_date:desc.
`limit`	No	Max rows (default 25, cap 100).
`naics`	No	NAICS code prefix(es), CSV (e.g. 23 = construction).
`since`	No	Approved on/after this date (YYYY-MM-DD) — the growth-capital recency window.
`state`	No	Borrower state code(s), CSV.
`lender`	No	Funding lender fragment — 7(a) bank name / 504 CDC name.
`offset`	No	Rows to skip.
`company`	No	Borrower (company) name — suffix/punctuation-insensitive.
`program`	No	7A = 7(a) guaranty, 504 = 504/CDC debenture.
`entity_id`	No	Resolved borrower entity UUID (pivots to business360).
`franchise`	No	Franchise name fragment.
`amount_max`	No	Maximum gross approval amount (USD).
`amount_min`	No	Minimum gross approval amount (USD).
`business_type`	No	Business type fragment (Corporation \| Individual \| Partnership).
`project_state`	No	Project (place-of-use) state code(s), CSV.

Schema Changelog

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

AddedJul 27, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the data source (FOIA) but lacks details on pagination, rate limits, or query behavior beyond parameter descriptions. It is adequate but not comprehensive.

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 dense and efficient, starting with an engaging question and logically listing fields. It has no wasted words, though a slightly more structured layout could improve readability.

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 the absence of an output schema, the description adequately covers both input filters and output fields. It provides enough context for the agent to understand the tool's capabilities, though missing details on result limits and default sort order.

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%, so baseline is 3. The description adds contextual meaning beyond schema, e.g., explaining 'since' as the growth-capital recency trigger and listing filters in a coherent manner, raising the score to 4.

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 the tool's purpose: searching the SBA 7(a) & 504 FOIA loan-approval roster. It lists specific filters and returned fields, clearly distinguishing it from sibling tools in other domains (CMS, FAA, etc.).

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 implies usage for retrieving SBA loan data, but does not explicitly state when to use it vs. alternatives or when not to use it. Given the clear domain separation from siblings, this is still effective.

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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