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UK Due Diligence

by io.github.paulieb89

Screen a Name Against Sanctions Lists

sanctions_screen
Read-onlyIdempotent

Screen a name against the UK (OFSI), US (OFAC), EU and UN consolidated sanctions lists.

Returns every list entry whose primary name or alias matches, with the regime, source reference and listing date. Use it to check whether a counterparty — or its officers / persons with significant control — appears on a sanctions list.

MATCHING is deterministic: normalised exact + alias match (case-, accent- and punctuation-insensitive). A company/entity legal name matches reliably; PERSON names with transliteration variants may not (e.g. 'Mohammed' vs 'Muhamad'). An empty result is therefore NOT a guarantee of clearance, and a hit on a common name may be a false positive to disambiguate. This is a screening aid, not a compliance determination.

lists_screened reports which of OFSI/OFAC/EU/UN were actually loaded — if any is missing the result is partial. as_at is when the lists were last refreshed on this server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPerson or company/entity name to screen against the consolidated sanctions lists.
entity_typeNoOptional filter: 'person' or 'entity'. Omit to screen both.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hitsNoMatching list entries. An empty list means no exact/alias match on the screened lists — NOT a guarantee of clearance (see the tool description on matching limits).
as_atNoWhen this server last refreshed the loaded lists (ISO timestamp). Provenance for the screen — the lists update on designation.
queryYesThe name that was screened.
match_countYesNumber of list entries that matched the query.
lists_screenedNoWhich consolidated lists were loaded and actually screened for this call. A list absent here failed to load and was NOT screened — treat the result as partial if any of OFSI/OFAC/EU/UN is missing.
normalized_queryYesThe normalised form used for matching (upper-cased, accent- and punctuation-stripped, whitespace-collapsed).
entity_type_filterNoentity_type filter applied to the screen ('person'/'entity'), or null.

Schema Changelog

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

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

The description adds rich behavioral detail beyond annotations: matching is deterministic and normalised (case/accent/punctuation insensitive), entity names match reliably but person names with transliteration variants may not, an empty result is not a guarantee of clearance, and false positives are possible. It also explains the meaning of 'lists_screened' and 'as_at' output fields. This substantially exceeds the annotations' readOnly/openWorld/idempotent hints.

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 well-structured and front-loaded: purpose, use case, matching behavior, caveats, and output fields. Every sentence contributes substantive information; there is no fluff or repetition. The length is justified by the complexity of the tool's behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (sanctions screening with nuanced matching and result interpretation) and the presence of an output schema, the description covers all critical aspects: which lists are screened, matching details, interpretation of results, and meaning of key output fields. It is complete and self-contained.

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 coverage is 100%, so baseline is 3. The description adds semantics for the 'name' parameter by explaining how matching behaves (normalised exact/alias match, transliteration caveats), which is not in the schema. It also clarifies that 'entity_type' filters person vs entity, consistent with the schema. This adds value beyond the structured field descriptions.

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 function: 'Screen a name against the UK (OFSI), US (OFAC), EU and UN consolidated sanctions lists.' It uses a specific verb ('screen') and specific resource (sanctions lists), and is distinct from sibling tools which focus on company/gazette/land data. The title reinforces the purpose.

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?

The description gives explicit usage context: 'Use it to check whether a counterparty — or its officers / persons with significant control — appears on a sanctions list.' It also provides important caveats about what the tool is not for: 'This is a screening aid, not a compliance determination.' While it doesn't name alternative tools (none exist among siblings), the when-to-use and when-not-to-use guidance is clear.

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

All UK Due Diligence toolsInspect
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TDQS

A4.2/5.0
Disambiguation4/5

The domain-specific tools are clearly distinct (search vs profile for each register), and the generic search/fetch tools are designed to route across them. Potential overlap between company_officers and company_psc is resolved by clear descriptions of officers vs beneficial ownership. Slight ambiguity exists between generic fetch/search and the domain-specific counterparts, but the routing logic is well-documented.

Naming Consistency4/5

Most tools follow a consistent resource_action pattern with clear prefixes (charity_, company_, disqualified_, gazette_). Exceptions like company_officers, company_psc, sanctions_screen, and vat_validate deviate from the verb-first convention, and generic tools (fetch, search, get_prompt, list_prompts) do not follow the pattern. Overall, the naming is readable and predictable despite a few outliers.

Tool Count4/5

With 17 tools, the server sits slightly above the typical 3-15 well-scoped range, but the breadth of the domain (Companies House, Charity Commission, disqualifications, Gazette insolvency, sanctions, land registry, VAT) justifies the count. Each tool serves a distinct data source or action, and the two prompt-management tools are standard MCP utilities. The count feels appropriate rather than excessive.

Completeness4/5

The server covers the core due diligence workflow: searching and retrieving profiles for companies, charities, and disqualified directors, plus insolvency notices, sanctions screening, land transactions, and VAT validation. Minor gaps exist, such as no direct tool for company accounts or court judgments, but these are not core to the apparent purpose and can be worked around.

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