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LiveDataLink

by io.github.blackboxfoundry

influence_network_map

Read-onlyIdempotent

One-call 'follow the money and influence' map for an organization, joined across three federal public-record streams: FEC (the org's connected political committees / PACs - its political-spending vehicles), the U.S. Senate Lobbying Disclosure Act (filings where the org is the client, the reported lobbying spend, the firms it hired, and the issue areas lobbied), and USAspending (federal contracts + grants the org RECEIVES, with award counts and top agencies). Returns a readable map of money flowing OUT to influence (lobbying + political committees) vs. money flowing IN from federal awards. Built for investigative journalism, govcon, and due-diligence research. Informational public-record synthesis, NOT a risk score (distinct from counterparty_risk_score). The FEC leg needs an api.data.gov key and is noted as skipped if unavailable; a source that fails is noted, not fatal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoOptional 4-digit lobbying filing year (e.g. '2024'); defaults to the most recent year with filings.
stateNoOptional 2-letter state to scope the FEC committee search.
companyNoAlias for organization.
organizationYesOrganization / company name (e.g. 'Lockheed Martin', 'Boeing').

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, open-world, and non-destructive behavior. The description adds meaningful behavioral context beyond that: the FEC leg requires an api.data.gov key, unavailable sources are reported as skipped rather than fatal, and the result is a synthesized readable map rather than a raw dataset.

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 dense but well-structured: purpose, sources, output shape, use cases, differentiation from a sibling, and operational caveat. Every sentence earns its place and the most important scoping information is front-loaded.

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 complex multi-source tool with no output schema, the description does a good job explaining what is joined, what the map compares, and what happens when a source is unavailable. It could be slightly more explicit about the output field structure and how the optional year/state parameters affect each data leg, but it is sufficient for an agent to invoke it correctly.

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?

The input schema already provides 100% coverage for all four parameters. The description reinforces the organization-level focus but does not add substantive parameter-level detail beyond what the schema documents, so a baseline score of 3 is appropriate.

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 clear verb and resource: a one-call 'follow the money and influence' map for an organization. It names the three data streams, the outbound vs. inbound money distinction, and explicitly separates itself from counterparty_risk_score, making it easy to distinguish from siblings.

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?

It states intended use cases (investigative journalism, govcon, due-diligence research) and explicitly says it is not a risk score, naming counterparty_risk_score as the distinct alternative. It could be stronger with more explicit 'use this instead of raw FEC/lobbying/spending searches' guidance, but the context is clear.

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

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.

Resources