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Glama

screen_sanctions

Read-onlyIdempotent

Free screening of a name or entity against official sanctions lists, each fetched from the authority that issues it: the OFAC SDN list from the US Treasury (SDN.CSV plus ALT.CSV for alternate spellings), the EU consolidated financial sanctions list from the European Commission, and the UK Sanctions List from the FCDO. THE UN CONSOLIDATED LIST IS NOT SCREENED -- it carries no licence permitting commercial redistribution, so we do not claim it. ALWAYS check lists_screened on the response: it names the lists that actually ran ON THAT CALL, and a list that failed to load appears in sources_unavailable instead. reason_code is 'partial_screening' whenever any source was unavailable, never 'clear'. Returns screening_status ('hit' | 'clean' | 'candidates' | 'not_screened' -- branch on THIS, not on matched, because matched:false is also false when nothing could be screened), matched: bool, a list of matches with score, program, and source URL, and which lists were screened. Never fabricates a match or a clear -- if no match is found, explicitly names which lists were checked. Attaches a compliance_receipt: an Ed25519-signed, hash-bound record of what was checked, when, against which sources, and what it returned - verifiable OFFLINE against the public key published at https://hatchloop.dev/agents.md, so you can hand it to an auditor as evidence the check really ran.

EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "Screen this vendor before we pay them: ACME Trading LLC, Russia" -> call screen_sanctions({"name": "ACME Trading LLC", "country": "RU", "type": "entity"}) user: "Is Kim Jong-un on the OFAC list?" -> call screen_sanctions({"name": "Kim Jong-un", "country": "KP", "type": "person"}) user: "Run a sanctions check on this person before onboarding" -> call screen_sanctions({"name": "Ivan Petrov", "country": "RU", "type": "person"}) user: "Do a compliance check -- is this company sanctioned?" -> call screen_sanctions({"name": "Mahan Air", "country": "IR", "type": "entity"})

WHEN TO USE: Use before onboarding a counterparty, processing a payment, engaging a vendor, or doing any due-diligence step that requires knowing whether a person or entity appears on official sanctions lists. Essential for agents doing business formation, vendor qualification, payments onboarding, trade compliance, or any workflow where a sanctioned counterparty is a legal or reputational risk. WHEN NOT TO USE: Do not use as a substitute for full KYC/AML screening -- this covers sanctions lists only, not PEP (Politically Exposed Person) databases, adverse media, or credit risk. Do not treat a negative result as a compliance clearance; it is informational only. Do not use for bulk screening of large lists -- each call is a live API query. COST: free within the daily quota, then $0.02 per call LATENCY: ~2000ms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesFull name of the person or entity to screen, e.g. 'Kim Jong-un' or 'ACME Trading LLC'. Use the most complete name available for best accuracy.
typeNoOptional entity type hint. 'person' for individuals, 'entity' for organizations/companies. Omit to screen both.
countryNoOptional ISO 3166-1 alpha-2 country code or country name (e.g. 'IR', 'Iran'). It ANNOTATES AND RANKS results; it never removes any. Each EU/UK match carries country_match: true, false, or null when the listing records no country. Nothing is dropped on a mismatch, because the country we hold is the address/nationality on the listing rather than everywhere a party operates - excluding on it would return a clean screen for someone who IS listed.

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / country / description
      Previous value: -"Optional ISO 3166-1 alpha-2 country code (e.g. 'US', 'RU', 'IR'). Narrows results to entities associated with this country."New value: +"Optional ISO 3166-1 alpha-2 country code or country name (e.g. 'IR', 'Iran'). It ANNOTATES AND RANKS results; it never removes any. Each EU/UK match carries country_match: true, false, or null when the listing records no country. Nothing is dropped on a mismatch, because the country we hold is the address/nationality on the listing rather than everywhere a party operates - excluding on it would return a clean screen for someone who IS listed."
  2. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds substantial behavior beyond them: the UN list is intentionally excluded for licensing reasons, lists_screened may vary per call, reason_code becomes 'partial_screening' on partial failure, and screening_status must be branched on instead of matched. It also discloses the compliance_receipt signing and the no-fabrication guarantee.

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?

Though detailed, the description is well-structured with headers, examples, and explicit cost/latency fields. Every section earns its place by addressing a real invocation risk: partial screening, false-clear semantics, and source attribution. The most decision-critical warning (never treat matched:false as clean) is front-loaded.

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?

With no output schema, the description fully carries the burden of explaining return values and failure modes: it names screening_status values, matched, matches structure, lists_screened, sources_unavailable, reason_code, and compliance_receipt. It also covers cost, latency, and response verification. Nothing an agent needs to call and interpret this tool correctly is missing.

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 description coverage is 100%, so baseline is 3. The tool description adds value by showing exact example mappings from natural-language queries to parameters and reinforces the country parameter's annotate-never-filter behavior, which prevents an agent from incorrectly using country as a hard filter.

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 specific verb and resource ('Free screening of a name or entity against official sanctions lists') and names the exact lists screened (OFAC, EU, UK). It is unmistakably distinct from generic tools like check_compliance by scoping the behavior to sanctions-only screening.

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?

Provides explicit 'WHEN TO USE' (onboarding, payments, vendor engagement, due diligence) and 'WHEN NOT TO USE' (not a substitute for full KYC/AML, not bulk screening, not a compliance clearance). It even gives concrete example user queries and their corresponding parameter mappings, leaving no ambiguity about when to invoke this tool.

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

A3.9/5.0
Disambiguation4/5

Most tools target distinct resource+action pairs (find_business vs verify_business, check_booking_link vs import_booking_url, get_status vs get_outcome). The main confusable pairs are send_message vs send_transactional_confirmation and verify_business vs verify_company_record, but their descriptions draw clear boundary lines.

Naming Consistency4/5

The set overwhelmingly follows lower_snake_case verb_noun naming (call_business, check_quota, find_business, send_message, verify_company_record). Minor deviations like self_test and mint_key, plus inconsistent verb choices (lookup_ vs get_ vs find_), prevent a perfect score.

Tool Count3/5

At 23 tools, the server falls into the heavy range and bundles several unrelated domains: SMB booking/messaging, trade and sanctions compliance, company verification, and platform operations. Each tool is individually reasonable, but the set feels like multiple servers merged into one.

Completeness3/5

Core SMB workflows are well covered: find/verify/import/book, messaging with conversation handling, and compliance preflights. Notable gaps include no consent-record management even though send_message requires consent_record_id for marketing, no update/delete lifecycle for leads or businesses, and no webhook configuration despite webhooks being referenced.