Skip to main content
Glama
lzinga

US Government Open Data MCP

by lzinga

lobbying_search

Read-onlyIdempotent

Search federal lobbying disclosure filings to identify who lobbies Congress, which issues they target, and how much they spend. Filter by lobbyist, client, issue area, or filing year to uncover influence and spending data.

Instructions

Search lobbying disclosure filings — find out who is lobbying Congress, on what issues, and how much they're spending.

Search by:

  • registrant_name: lobbying firm or self-filing org ('Pfizer', 'Amazon', 'National Rifle Association')

  • client_name: who hired the lobbyist ('Google', 'ExxonMobil')

  • issue_code: policy area ('TAX', 'HCR' health, 'DEF' defense, 'ENV' environment, 'ENG' energy, 'IMM' immigration)

  • filing_year: year of filing (2020-2026)

Returns expenses/income amounts, issues lobbied, and registrant/client info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
page_sizeNoResults per page (default 20)
issue_codeNoIssue area code: 'HCR' (Health Issues), 'MMM' (Medicare/Medicaid), 'TAX' (Taxation/Internal Revenue Code), 'BUD' (Budget/Appropriations), 'DEF' (Defense), 'ENV' (Environment/Superfund), 'ENG' (Energy/Nuclear), 'TRD' (Trade (Domestic/Foreign)), ... (20 total)
client_nameNoClient who hired the lobbyist: 'Google', 'Meta', 'Boeing'
filing_typeNoFiling type: 'Q1' (1st Quarter Report), 'Q2' (2nd Quarter Report), 'Q3' (3rd Quarter Report), 'Q4' (4th Quarter Report), 'MM' (Mid-Year Report), 'MY' (Year-End Report), 'RN' (Registration (New)), 'RA' (Registration Amendment), 'RR' (Registration Renewal), 'TE' (Termination)
filing_yearNoYear: 2020-2026
registrant_nameNoLobbying firm or organization: 'Pfizer', 'Amazon', 'US Chamber of Commerce'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / page_size / default
      Added value: +20
  2. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv2026.3.9

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare this as read-only and non-destructive, so the description's job is to add behavioral value beyond that. It does so by specifying the return contents—expenses/income amounts, issues lobbied, and registrant/client info—which is useful because no output schema is provided. No annotation contradiction exists.

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 well structured and front-loaded: the core action and value statement appears first, then the key filter fields in a scannable list, and finally a concise return summary. Every sentence contributes useful guidance with minimal filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a moderate-complexity search tool with fully documented parameters and read-only annotations, the description is complete enough. It covers the search dimensions, gives concrete expected inputs, and summarizes the output fields, which matters because there is no output schema.

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%, so the description is not required to re-explain every parameter. It does add helpful plain-language examples and groups the primary filters, but it largely overlaps with the schema's own descriptions rather than adding substantially deeper semantics.

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 specific action and resource: 'Search lobbying disclosure filings.' It further clarifies what the tool helps an agent learn—who is lobbying Congress, on what issues, and how much is being spent—which clearly distinguishes it from sibling tools like lobbying_detail, lobbying_registrants, or lobbying_lobbyists.

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 for using the tool by listing the main searchable dimensions (registrant, client, issue code, and filing year) and what the search returns. It does not explicitly name alternatives or state when not to use this tool, but the purpose is specific enough that the intended use case is evident.

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

Deploy Server

Other Tools