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LiveDataLink

by io.github.blackboxfoundry

sanctions_search_alias

Read-onlyIdempotent

Search aliases / AKAs across selected lists. Distinct from screen_entity in that only the alias fields are matched, which is helpful when the primary listed name differs sharply from the popular spelling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum matches to return. Defaults vary per tool.
queryYesAlias / AKA to search for.
sourcesNoRestrict screening to a subset of source lists. Defaults to all four. Allowed: OFAC_SDN, EU_CFSP, UN_SC, BIS_DPL.
thresholdNoMinimum confidence score (0..1) for a result to be returned. Defaults to 0.85.

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful behavior context — that only alias fields are matched — but does not describe return shape, pagination, or other runtime behavior. This is adequate but not rich.

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?

Two sentences with no filler. The action and scope are front-loaded, and the second sentence earns its place by preventing confusion with the closely related screen_entity tool.

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 read-only, fully schema-documented search tool, the description covers what it does, how it differs from its closest sibling, and when it is best used. It does not describe output shape, but with no output schema and a straightforward search use case, this is a minor gap rather than a blocking one.

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 schema fully documents query, limit, sources, and threshold. The description's alias-focused wording adds semantic framing for query but no additional parameter-level detail beyond the schema. Baseline 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 uses a specific verb and resource ('Search aliases / AKAs across selected lists') and explicitly distinguishes the tool from screen_entity by noting that only alias fields are matched. This makes the tool's purpose and scope immediately clear.

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

Usage Guidelines5/5

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

It names the alternative (screen_entity) and explains when this tool is helpful: when the primary listed name differs sharply from the popular spelling. That is an explicit routing signal for an agent deciding between related sanctions tools.

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