SanctionScreen

io.sanctionsscreenPublished by sanctionsscreen.ioOfficial publisherv1.0.0Updated Oct 24, 2026

Screen counterparties and enrich companies for AI agents — sanctions checks, cited sources.

VerifiedStreamable HTTPWeb executableSecurity & MonitoringBusiness & Commerce

Overview

AI-generated overview

A remote MCP server that lets an assistant screen counterparty names against sanctions lists and look up company facts from the GLEIF LEI registry.

What you can do
Screen a counterparty name against indexed sanctions lists (OFAC SDN, UK FCDO consolidated), with normalization and transliteration tolerant of token order and spelling variants, returning cited sources and match details for review rather than a bare yes or no.
When to use it
Useful when an assistant needs a quick sanctions screening or company identity check during onboarding, vendor due diligence, or compliance review, and the results will be reviewed by a person.
Requirements
A remote endpoint at api.sanctionsscreen.io over streamable HTTP. A SanctionScreen API key (cs_live_ prefix) is required and sent as a Bearer token in the Authorization header. Network access is needed.
Before you install
The API key is a live credential sent in the Authorization header; keep it out of logs and shared transcripts. Screening results are name-matching aids, not legal determinations, so confirm matches before acting. Company enrichment relies on the public GLEIF registry and may return limited or no data.

Installation

In SourceWeft

  1. Open SanctionScreen in the dashboard and add it to a workspace.
  2. Connect Authorization token credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.sanctionsscreen%2Fsanctionscreen/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "sanctionscreen": {
      "type": "http",
      "url": "https://api.sanctionsscreen.io/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

Tools

2

screen_counterparty

Screen a counterparty name against the indexed sanctions lists (OFAC SDN, UK FCDO consolidated). What it does: normalizes the query (Unicode NFKD fold, punctuation strip, lowercase, Cyrillic/Greek transliteration; tolerant to token order e.g. "Putin Vladimir" vs "Vladimir Putin"), looks it up in the sanctions index, and returns EVERY match at low confidence or above with a per-match citation. Low-confidence matches are never hidden. Inputs: - name (required, string): full name of the person or entity. - country (optional, ISO-3166 alpha-2, e.g. "RU"): corroborates nationality/citizenship identifiers. - dob (optional, "YYYY-MM-DD"): a dob match adds +15 to the score — the strongest corroborator. - identifiers (optional, [{type, value}]): extra identifiers to check against the record, e.g. [{"type":"passport","value":"719023441"}]. - request_id (optional, string): idempotency key; safe to retry. - include_low_confidence (optional, boolean, default true): fuzzy matches (Jaro-Winkler >= 0.92) land in the low tier. Keep true — hiding low matches is a compliance liability. Output: {screening_id, disposition, matches[], disclaimer, generated_at}. - disposition: "clear" (no matches) | "potential_match" (any medium/low match) | "review_advised" (any high-confidence match — human review required before any adverse action). - Each match: {list, list_date, record_uid, matched_name, name_kind (primary|alias_strong|alias_weak), confidence (high|medium|low), confidence_score (0-100), matched_fields, citation {source, url, accessed_at}}. - Confidence math: exact primary 80 / alias_strong 70 / alias_weak 55; dob match +15. Tiers: high >= 85, medium >= 60, low >= 30. Fuzzy (JW >= 0.92) -> low tier, score 30-55. - LANGUAGE RULE: report "potential match", never "sanctioned". Screening is informational only — not a legal verdict. Every response carries the fixed disclaimer. EXAMPLE 1 — listed individual with corroborating dob: Input: {"name": "Vladimir Putin", "dob": "1952-10-07",

Parametersdobnamerequiredcountryrequest_ididentifiersinclude_low_confidence

enrich_company

Resolve a company domain or legal name to structured company facts via the free public GLEIF LEI registry. Inputs: {domain? e.g. "apple.com", name? e.g. "Apple Inc.", request_id? (idempotency)}. At least one of domain/name is required. v1 boundaries (returned honestly, never invented): - GLEIF has no domain index: domain-only lookups are best-effort (registrable-name candidates are tried). Provide the legal company name for reliable resolution. - GLEIF does not publish industry, industry_code, size_band, or employee_range: those come back null, each with a sources[] entry documenting the gap. - founded is the legal-entity creation date (GLEIF publishes no true founding date). - Unresolvable input -> tool error with code UNRESOLVABLE. Output: {company_id, legal_name, domain, industry, industry_code, size_band, employee_range, hq: {country, city}, founded, sources: [{field, source, url}], confidence, generated_at}. EXAMPLE 1: Input: {"domain": "apple.com", "request_id": "demo-e1"} Output: {"company_id": "cs_co_...", "legal_name": "Apple Inc.", "domain": "apple.com", "industry": null, "industry_code": null, "size_band": null, "employee_range": null, "hq": {"country": "US", "city": "Cupertino"}, "founded": "1980-12-12", "sources": [{"field": "legal_name", "source": "GLEIF LEI (api.gleif.org)", "url": "https://api.gleif.org/api/v1/lei-records/..."}, {"field": "industry", "source": "GLEIF LEI — field not published by GLEIF (null by design in v1)", "url": "https://api.gleif.org/api/v1/lei-records/..."}], "confidence": "high", "generated_at": "2026-09-26T...Z"} EXAMPLE 2 — unresolvable: Input: {"name": "Nonexistent Widgets Pty Ltd ZZ"} Tool error: {"code": "UNRESOLVABLE", "message": "No GLEIF LEI record matched ..."}

Parametersnamedomainrequest_id

Version history

1
  1. v1.0.0LatestSep 26, 2026

Score

72% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts

    Publish an icon in the registry entry.

  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.