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lzinga

US Government Open Data MCP

by lzinga

lobbying_lobbyists

Read-onlyIdempotent

Find specific lobbyists by name or firm to identify who lobbies Congress and which firms they work for.

Instructions

Search individual lobbyists by name or firm. Find specific people who lobby Congress and which firms they work for.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
firmNoLobbying firm name: 'Akin Gump', 'K Street'
nameNoLobbyist name (partial match): 'Smith', 'Johnson'
page_sizeNoResults per page (default 20)

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

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, so the description does not need to restate safety. It adds a hint about output (which firms they work for) but does not disclose pagination behavior, result limits, or any other operational details. This is acceptable given the strong annotation coverage, but the description adds minimal extra behavioral context.

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 two short sentences with no wasted words. The primary action and target are front-loaded, and the second sentence clarifies the output intent. Every phrase contributes to understanding.

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 simple search tool with only three optional parameters and no output schema, the description adequately conveys the purpose and expected result (finding lobbyists and their firms). It does not mention pagination or potential large result sets, but given the simplicity and the absence of an output schema, it is reasonably complete.

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% with all three parameters (firm, name, page_size) having descriptions. The tool description mentions 'by name or firm', which maps to the name and firm parameters, but does not add any new meaning or format details beyond the schema. Per the rubric, a baseline of 3 is appropriate when schema already documents parameters fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Search' and the resource 'individual lobbyists', and specifies the search dimensions (by name or firm). It differentiates from siblings like lobbying_registrants (which likely targets firms) by emphasizing individuals. However, it does not explicitly name any sibling tools, so it falls just short of a 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as lobbying_search or lobbying_registrants. It does not state any exclusions or conditions, leaving the agent to infer usage from the name and description alone.

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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