Skip to main content
Glama
lzinga

US Government Open Data MCP

lobbying_search

Read-only

Search lobbying disclosure filings by registrant, client, issue, or year to uncover who is lobbying Congress, on what issues, and total spending.

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
registrant_nameNoLobbying firm or organization: 'Pfizer', 'Amazon', 'US Chamber of Commerce'
client_nameNoClient who hired the lobbyist: 'Google', 'Meta', 'Boeing'
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)
filing_yearNoYear: 2020-2026
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)
page_sizeNoResults per page (default 20)
Behavior3/5

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

The description aligns with the readOnlyHint annotation by describing a search operation. However, it does not disclose additional behavioral traits such as pagination (page_size parameter is present but not explained in behavior), rate limits, or how results are ordered. The description adds no new behavioral context beyond the annotation.

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 well-structured with a clear opening sentence and bullet points for search parameters. It is concise enough to convey all necessary information without excessive verbosity. The use of examples in-line is efficient.

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 mentions return values ('expenses/income amounts, issues lobbied, and registrant/client info'), which partially compensates. The parameter coverage is complete. However, it could be more complete by noting that results are paginated and the default page size.

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%, so baseline is 3. The description adds value by providing concrete examples for registrant_name, client_name, issue_code (with expanded examples of policy areas), and filing_year. This helps the agent understand acceptable input formats beyond the schema's type definitions.

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 purpose: 'Search lobbying disclosure filings — find out who is lobbying Congress, on what issues, and how much they're spending.' It specifies the resource (lobbying filings) and actions (search), and distinguishes itself from sibling tools like lobbying_contributions, lobbying_detail, lobbying_lobbyists, and lobbying_registrants by focusing on filing searches.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides examples of how to use the tool with parameters but does not explicitly state when to use this tool over alternatives. For instance, it doesn't differentiate from lobbying_detail or lobbying_registrants. The guidance is implied through the parameter descriptions, but no explicit 'when to use' or 'when not to use' is given.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/lzinga/us-gov-open-data-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server