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Didit Aml

didit_aml
Read-onlyIdempotent

Screen a person (or entity) against 1,300+ global sanctions, PEP, watchlist, and adverse-media lists using the Didit AML API. Returns an overall status + risk score plus each individual hit (sanctions/PEP/adverse-media matches). Example: didit_aml({ full_name: "Vladimir Putin", date_of_birth: "1952-10-07", nationality: "RU", _apiKey: "your-key" })

Input Schema

NameRequiredDescriptionDefault
_apiKeyYesDidit API key. Get one at https://didit.me/pricing (docs: https://docs.didit.me/).
full_nameYesFull name of the person or entity to screen, e.g. "Antonio Ejemplo Modelo"
entity_typeNoOptional: "person" (default) or "company".
nationalityNoOptional ISO 3166-1 alpha-2 country/nationality code, e.g. "ES", "US". Also accepted as `country`.
date_of_birthNoOptional date of birth in YYYY-MM-DD format, e.g. "1972-02-29". Improves match precision.
document_numberNoOptional government ID / document number for higher-confidence matching.
include_adverse_mediaNoInclude adverse-media screening. Adds ~10s to the request. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds a useful detail that adverse-media screening adds latency (though that's actually in the schema) and describes the return shape (overall status + risk score + individual hits). This is helpful but not rich behavioral context; with annotations doing the safety work, a 3 fits.

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?

Two sentences, front-loaded with the core purpose, followed by return-value context and a concrete example. The example is useful for an agent but slightly lengthens the description; no real waste, though the closing quote appears to be a typo rather than intended content.

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, idempotent screening tool with a fully documented schema and no output schema, the description covers purpose, return shape, and a working example. It's complete enough to invoke correctly, though it could note rate limits or latency for the main call.

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 already documents all 7 parameters with examples and formats. The description's example invocation reinforces usage but adds no semantic detail beyond what the schema provides. Baseline 3 is appropriate when the schema carries the full parameter burden.

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?

States a specific verb (Screen) and resource (person/entity against 1,300+ sanctions/PEP/watchlist/adverse-media lists), and frames it as the Didit AML API operation. An agent can distinguish this from the sibling didit_kyb (business verification) based on the resource screened.

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 implies usage (screening a person or entity) but offers no explicit when-to-use guidance or comparison to the sibling didit_kyb. There's no statement of exclusions or prerequisites for when AML screening is appropriate versus KYB.

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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