Skip to main content
Glama

Govparse Government Data Gateway

by io.govparse

get_leads

Get the actual B2B leads for a Parse: the matching companies and the public-record events that flagged them (real rows, including any free native contacts on the source record). PAID, priced PER LEAD RETURNED — connect with your API key (metered key billed per lead, or a SaaS key covered by your plan's lead entitlement) or pay keyless with an x402 USDC payment on Base or Solana (prepaid for up to limit leads). Compose the Parse with build_parse first, then pass its parse here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows per page (default 25, max 100).
parseNoAlternatively, the `parse` object returned by build_parse — replays the exact composed intent so a preview and its paid pull match.
queryNoOPTIONAL value-prop LABEL only (what you sell) — it does NOT select the Parse and is never inferred. The Parse is composed ONLY from an explicit selection: a `preset_id`, or `target_entity` + `buying_moments`.
offsetNoRow offset for paging (default 0).
statesNoTwo-letter US state codes to scope to; empty = nationwide.
industryNoAn industry slug from list_industries (e.g. "freight-factoring", "pharma-sales") — scopes/labels the pick. Not a selector on its own.
preset_idNoAlternatively, a curated-Parse or preset id (from list_industries) to compose a proven Parse.
attributesNoIdeal-customer descriptors, e.g. ["small / emerging", "multi-location"].
target_entityNoStructured pick: the entity you SELL TO. Taken verbatim (never guessed), so a pharma-brand seller can't be mis-targeted onto physicians.
buying_momentsNoStructured pick: library template ids (buying-moment ids) from build_parse/list_industries output. Each maps to a real signal.

Schema Changelog

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

  1. Changed3 schema fields changed
    • changedInput schema / description
      Previous value: -"A Parse (build_parse output `parse`, a `preset_id`, a plain `query`, or the structured fields) plus optional paging."New value: +"A Parse selected EXPLICITLY (a build_parse output `parse`, a `preset_id`, or structured {target_entity, buying_moments[]}) plus optional paging. `query` alone does not select a Parse."
    • changedInput schema / properties / industry / description
      Previous value: -"Structured pick: an industry slug from list_industries (e.g. \"freight-factoring\", \"pharma-sales\"). Free text is also accepted."New value: +"An industry slug from list_industries (e.g. \"freight-factoring\", \"pharma-sales\") — scopes/labels the pick. Not a selector on its own."
    • changedInput schema / properties / query / description
      Previous value: -"Plain-English description of what you sell and who you target, e.g. \"I sell factoring to brand-new trucking carriers\". Either this OR the structured fields below."New value: +"OPTIONAL value-prop LABEL only (what you sell) — it does NOT select the Parse and is never inferred. The Parse is composed ONLY from an explicit selection: a `preset_id`, or `target_entity` + `buying_moments`."
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden and meets it well. It discloses the tool is PAID and priced per lead returned, explains the payment methods (API key or x402 USDC prepaid up to `limit`), clarifies that `query` alone does not select a Parse, and explicitly states it returns 'real rows' rather than a preview. This is high-value behavioral context beyond the schema.

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 three sentences with no filler: it front-loads the purpose, then covers cost/payment, then gives the workflow prerequisite. Every sentence contributes essential information, making it appropriately sized and well-structured.

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 tool with 10 parameters, no annotations, and no output schema, the description provides enough context for an agent to understand what to expect: actual companies, events, and contacts. It also explains the prerequisite workflow and pricing model. The schema covers all parameter details. It lacks an explicit return schema or pagination behavior, but the given context is sufficient for decision-making.

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 description coverage is 100% with detailed explanations for all 10 parameters, which sets a baseline of 3. The description adds useful semantics by linking `limit` to prepayment ('prepaid for up to `limit` leads') and by clarifying the role of the `parse` parameter in the workflow ('pass its `parse` here'). These are meaningful additions beyond the schema.

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's verb and resource: 'Get the actual B2B leads for a Parse'. It specifies what the results include ('matching companies and the public-record events that flagged them, including any free native contacts') and distinguishes itself from the prerequisite build_parse by framing the workflow ('Compose the Parse with build_parse first, then pass its `parse` here').

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 gives an explicit usage workflow: build the Parse first, then pass its `parse` object. It also explains payment options (API key or USDC) and that the tool is paid per lead. However, it does not explicitly state when not to use this tool or mention alternatives beyond build_parse, such as using preset_id or list_industries directly, which are covered in the schema but not in the description.

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

All Govparse Government Data Gateway toolsInspect
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

A4.2/5.0
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