Govparse Government Data Gateway

oflc_sponsor_search

Which employers sponsor work visas or green cards? Search DOL OFLC disclosure data by employer name, state, program (LCA/H-1B vs PERM), case status, fiscal year, or SOC occupation code. Returns per-employer filing counts (total, LCA, PERM, certified, denied) — the shortlist behind 'who sponsors H-1B for this role?' [price: $0.05/row]

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	Employer name fragment, punctuation-insensitive. Example: 'amazon'.
`limit`	No	Max rows (default 25, cap 100).
`state`	No	Employer HQ state code(s), CSV. Example: 'WA,CA'.
`offset`	No	Rows to skip, for paging.
`program`	No	LCA (H-1B and related) \| PERM (green-card labor certification). CSV for both.
`soc_code`	No	Only sponsors with LCA filings in this SOC occupation. Example: 15-1252 (software developers).
`case_status`	No	CERTIFIED \| DENIED \| WITHDRAWN \| CERTIFIED - WITHDRAWN, CSV for multiple.
`fiscal_year_max`	No	Latest federal fiscal year to include.
`fiscal_year_min`	No	Earliest federal fiscal year to include.

Schema Changelog

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

First observedJul 24, 2026

TDQS

A4.1/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the return structure ('per-employer filing counts') and pricing ($0.05/row), which is helpful. It implies a read-only search operation with no destructive behavior.

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 concise at two sentences, front-loading the key question and search capabilities. It includes pricing without redundancy. Minor structure improvements could separate return details.

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 complexity (9 parameters, no output schema), the description covers the return format and key query dimensions. It lacks details on sorting or defaults but is sufficient for a search 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?

Schema description coverage is 100%, and the description does not add significant meaning beyond what the schema provides. The high-level summary is adequate but not compensatory.

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 the tool searches DOL OFLC disclosure data by employer name, state, program, etc., and returns per-employer filing counts. It distinguishes itself from siblings like 'oflc_sponsor_dossier' and 'oflc_stats_sponsors' by focusing on aggregated sponsor search results.

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 a concrete use case ('who sponsors H-1B for this role?') and lists queryable parameters. However, it does not explicitly mention when not to use this tool or compare it to sibling tools.

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.

Resources

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