Crypto Compliance Intelligence MCP Server

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Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf):

{
  "mcpServers": {
    "crypto-compliance-intelligence-mcp": {
      "url": "https://ryanclinton--crypto-compliance-intelligence-mcp.apify.actor/mcp"
    }
  }
}

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Crypto compliance intelligence for AI agents — sanctions screening, corporate verification, shell company detection, and regulatory tracking via the Model Context Protocol. This MCP server connects directly into Claude, Cursor, Windsurf, or any MCP-compatible client, giving your AI agent live access to 7 authoritative data sources: OFAC, OpenSanctions, OpenCorporates, GLEIF, CoinGecko, the Federal Register, and congressional bill tracking.

The server runs on Apify in Standby mode, processing requests as your agent makes tool calls. Parallel data fetching across all sources means a full due diligence report on a crypto entity returns in seconds, not hours. No infrastructure to manage, no subscription required — pay only for the queries you run.

What data can you access?

| Data Point | Source | Example |
|---|---|---|
| 📋 OFAC SDN list hits (including wallet addresses) | US Treasury OFAC | Tornado Cash: 1 SDN designation — BLOCKED |
| 🌐 International sanctions matches | OpenSanctions (100+ programs) | 3 matches: EU, UN, OFSI lists |
| 🪙 Token market data (price, volume, market cap) | CoinGecko | BTC: $67,432 / 24h vol $38B |
| 🏢 Corporate entity registrations | OpenCorporates (140+ jurisdictions) | Binance Holdings Ltd — KY active |
| 🔖 GLEIF Legal Entity Identifier | GLEIF global registry | LEI: 2138008L1QN44RNQUI78 — verified |
| 📜 Federal Register rulemakings | Federal Register (SEC, CFTC, FinCEN) | 12 final rules: MiCA-aligned stablecoin guidance |
| 🏛️ Congressional crypto bills | Congress.gov | 7 bills: Lummis-Gillibrand advanced to Senate floor |
| 🚨 Entity Compliance Risk Score | Composite (4 models) | Score: 73/100 — HIGH risk |
| 🏚️ Shell company detection level | Corporate + LEI analysis | LIKELY_SHELL — 2 offshore jurisdictions |
| 📊 Regulatory Velocity Index | Federal Register + Congress | Score: 61/100 — FAST regulatory change |
| ✅ Due diligence verdict | Composite scoring engine | ENHANCED_DUE_DILIGENCE |
| ⚡ Required compliance actions | Signal aggregation | File SAR, request beneficial ownership |

Why use Crypto Compliance Intelligence MCP Server?

Manual crypto compliance work is slow, expensive, and fragmented. A compliance analyst checking a single counterparty across OFAC, international sanctions lists, corporate registries, and regulatory filings might spend 2-3 hours per entity — and still miss connections between data sources. Commercial platforms like Chainalysis KYT or Elliptic charge $1,000-10,000/month before you run a single check.

This MCP server collapses multi-source due diligence into a single tool call. Your AI agent dispatches parallel queries across all relevant data sources, applies four scoring models, and returns a structured verdict with actionable signals — in under 30 seconds per entity. At $0.045 per tool call, a team screening 100 counterparties per month spends $4.50.

- Scheduling — run recurring entity screens on cadence to catch sanctions updates and new enforcement actions
- API access — trigger compliance checks from Python, JavaScript, or any HTTP client without MCP infrastructure
- Proxy rotation — underlying actors use Apify's proxy infrastructure to ensure data retrieval at scale
- Monitoring — get Slack or email alerts when compliance runs fail or produce unexpected results
- Integrations — connect to Zapier, Make, Google Sheets, HubSpot, or webhooks for downstream workflows

Features

- Seven-source parallel intelligence — OFAC, OpenSanctions, CoinGecko, OpenCorporates, GLEIF, Federal Register, and Congress Bills queried simultaneously via Promise.allSettled, ensuring partial results are never lost if one source is slow
- Entity Compliance Risk Score (0-100) — composite metric combining OFAC hits (weighted 40%), international sanctions (25%), shell indicators (20%), and LEI absence penalty (15%)
- OFAC automatic block — any OFAC SDN match triggers BLOCKED status and FAIL verdict regardless of composite score; blockers are surfaced as a separate array
- Shell company detection — five-signal algorithm scoring inactive entity ratio, high-risk jurisdiction count (Cayman Islands, BVI, Panama, Belize, Seychelles, Marshall Islands, Western Samoa, Vanuatu, Anguilla), multi-jurisdiction complexity, and GLEIF registration absence
- Regulatory Velocity Index (0-100) — measures pace of US crypto regulation from Federal Register final rules, proposed rules, and congressional bill advancement; levels STATIC through RAPID
- Project legitimacy scoring — cross-references CoinGecko market listing (35 pts), corporate registry presence (35 pts), and LEI verification (30 pts) to assess whether a token project has verifiable legal substance
- Enforcement action monitoring — scans Federal Register titles for "enforcement", "penalty", "settlement", and "cease" keywords; surfaces enforcement count separately from general rulemaking
- Full compliance report tool — generate_compliance_report runs all 7 actors and all 3 scoring models, returning composite score, verdict, all signals, required actions, and blockers in a single structured JSON
- Four due diligence verdicts — PASS, CONDITIONAL (score 15-34), ENHANCED_DUE_DILIGENCE (score 35-59), FAIL (score 60+, shell detected, or OFAC hit)
- Spending limit enforcement — every tool call checks Actor.charge() before executing; returns a structured error if the per-run budget is exhausted rather than silently failing
- MCP Standby mode — server stays warm on Apify infrastructure, responding to tool calls with minimal latency without cold-start delays per request
- Jurisdiction risk taxonomy — 9 high-risk offshore jurisdictions hardcoded: KY, VG, PA, BZ, SC, MH, WS, VU, AI; each entity registration in these jurisdictions adds 10 points to shell score

Use cases for crypto compliance intelligence

Exchange KYC/AML counterparty screening

Compliance teams at crypto exchanges use screen_crypto_entity during onboarding to satisfy MiCA Article 83 and FinCEN CDD Rule requirements. A single tool call returns OFAC status, OpenSanctions hits, corporate structure, and LEI verification — the four pillars of a defensible counterparty file. Automated screening at onboarding eliminates the manual checklist and creates an auditable JSON record per entity.

DeFi protocol partnership due diligence

Protocol teams evaluating institutional integrations need to verify that counterparties are not sanctioned entities operating through shell structures. verify_corporate_structure combined with check_sanctions_exposure surfaces dissolved entities, offshore complexity, and missing LEI registration before agreements are signed. This reduces legal exposure and satisfies investor LP requirements for institutional DeFi.

Crypto venture capital pre-investment screening

VC funds investing in digital asset projects face regulatory scrutiny over whether portfolio companies have verifiable corporate substance. assess_project_legitimacy cross-references CoinGecko market listing against corporate registry records and GLEIF LEI, producing a legitimacy score (0-100) that supports investment committee documentation. Funds screening 20 projects per month spend less than $1.

Regulatory change monitoring for compliance officers

Compliance officers at regulated crypto businesses need early warning of Federal Register rulemakings and congressional bills that affect their programs. track_crypto_regulation with topics like "stablecoin", "DeFi", or "exchange licensing" returns a Regulatory Velocity Index and full document list, enabling teams to prioritize program updates before final rules take effect.

Enforcement action intelligence

Legal and compliance teams tracking SEC, CFTC, and FinCEN enforcement patterns use monitor_enforcement_actions to surface relevant actions in the Federal Register. Filtering by sector (exchange, stablecoin, DeFi) identifies regulatory focus areas and helps teams assess their own exposure relative to enforcement trends.

Ongoing counterparty monitoring via AI agents

AI agents integrated into compliance workflows can run periodic re-screening of existing counterparties by calling screen_crypto_entity on a schedule. Score changes over time — a counterparty moving from CLEAR to MODERATE — trigger alerts via webhooks, enabling proactive risk management rather than point-in-time screening.

How to use crypto compliance intelligence

1. Connect the MCP server — Add the server URL to your MCP client configuration (see connection examples below). No code deployment required — the server runs on Apify infrastructure.
2. Configure your API token — Pass your Apify API token as a Bearer token in the Authorization header. Obtain a token at console.apify.com/account/integrations.
3. Call a tool — Ask your AI agent: "Screen Binance for compliance risk" or "Generate a compliance report on Nexo." The agent selects the appropriate tool and returns structured results.
4. Act on results — The server returns a verdict (PASS / CONDITIONAL / ENHANCED_DUE_DILIGENCE / FAIL), a numeric score, and a list of required actions. Download the full JSON from the Apify dataset for your compliance records.

MCP tools

| Tool | Price | Parameters | Description |
|---|---|---|---|
| screen_crypto_entity | $0.045 | entity (required), jurisdiction (optional) | OFAC + OpenSanctions + OpenCorporates + LEI. Returns Entity Compliance Risk Score (0-100) and compliance signals. |
| check_sanctions_exposure | $0.045 | entity (required) | OFAC SDN list + OpenSanctions global lists. Any OFAC match triggers BLOCKED status automatically. |
| verify_corporate_structure | $0.045 | entity (required), jurisdiction (optional) | OpenCorporates entity search + GLEIF LEI. Shell company detection score and 5-level classification. |
| track_crypto_regulation | $0.045 | topic (required) | Federal Register + Congress Bills. Regulatory Velocity Index (0-100) with proposed/final rule counts. |
| assess_project_legitimacy | $0.045 | project (required), token (optional) | CoinGecko + OpenCorporates + GLEIF. Legitimacy score (0-100) from market, corporate, and LEI signals. |
| monitor_enforcement_actions | $0.045 | entity (optional), sector (optional) | Federal Register enforcement keyword scan + congressional activity. Enforcement action count. |
| generate_compliance_report | $0.045 | entity (required), jurisdiction (optional) | All 7 data sources. Composite score, verdict, all signals, required actions, blockers. Full due diligence record. |

Connection examples

Claude Desktop (claude_desktop_config.json):

{

  "mcpServers": {

    "crypto-compliance": {

      "url": "https://actors-mcp-server.apify.actor/mcp?actors=ryanclinton/crypto-compliance-intelligence-mcp&token=YOUR_APIFY_TOKEN"

    }

  }

}

Direct Standby URL:

{

  "mcpServers": {

    "crypto-compliance": {

      "url": "https://ryanclinton--crypto-compliance-intelligence-mcp.apify.actor/mcp",

      "headers": {

        "Authorization": "Bearer YOUR_APIFY_TOKEN"

      }

    }

  }

}

Cursor / Windsurf / Cline — use the same URL format above in your MCP settings panel.

Tool call examples

Screen a crypto exchange for compliance risk:

{

  "tool": "screen_crypto_entity",

  "arguments": {

    "entity": "Nexo Financial",

    "jurisdiction": "bg"

  }

}

Full due diligence report:

{

  "tool": "generate_compliance_report",

  "arguments": {

    "entity": "Binance Holdings Limited",

    "jurisdiction": "ky"

  }

}

Track stablecoin regulation velocity:

{

  "tool": "track_crypto_regulation",

  "arguments": {

    "topic": "stablecoin reserve requirements"

  }

}

Input tips

- Provide full legal entity names — "Binance Holdings Limited" returns better corporate registry results than "Binance"; use the registered name where known
- Supply jurisdiction codes for corporate verification — two-letter ISO codes like "ky" (Cayman Islands), "vg" (BVI), "us", "gb" narrow OpenCorporates results dramatically
- Use token symbols for legitimacy assessment — pass token: "NEXO" alongside project: "Nexo Financial" so CoinGecko lookup uses the exact ticker rather than a fuzzy name search
- Scope enforcement monitoring by sector — "DeFi", "stablecoin", or "exchange" in the sector parameter focuses Federal Register results; omitting both entity and sector returns broad crypto enforcement trends
- Run generate_compliance_report for documented due diligence — the composite report is the most cost-efficient option when you need the full evidence record; individual tools are faster for single-question spot checks

Output example

Response from generate_compliance_report for entity "Acme Digital Holdings":

{
  "entity": "Acme Digital Holdings",
  "compositeScore": 47,
  "verdict": "ENHANCED_DUE_DILIGENCE",
  "entityCompliance": {
    "score": 38,
    "ofacHits": 0,
    "sanctionsHits": 2,
    "shellIndicators": 8,
    "riskLevel": "MODERATE",
    "signals": [
      "2 international sanctions matches — enhanced due diligence required",
      "Shell company indicators: high-risk jurisdictions, dissolved entities, complex structure",
      "No GLEIF LEI found — entity not registered with Legal Entity Identifier system"
    ]
  },
  "regulatoryVelocity": {
    "score": 54,
    "totalRegulations": 11,
    "proposedRules": 4,
    "finalRules": 3,
    "congressBills": 6,
    "velocityLevel": "MODERATE",
    "signals": [
      "3 final rules — regulatory framework hardening",
      "4 proposed rules — more regulation incoming",
      "6 crypto-related bills in Congress — active legislative agenda"
    ]
  },
  "shellDetection": {
    "score": 55,
    "entityCount": 4,
    "inactiveEntities": 2,
    "highRiskJurisdictions": 2,
    "leiVerified": false,
    "detectionLevel": "SUSPICIOUS",
    "signals": [
      "2 dissolved/inactive entities — corporate graveyard pattern",
      "2 entities in high-risk offshore jurisdictions",
      "No LEI registration — entity avoids transparency framework"
    ]
  },
  "allSignals": [
    "2 international sanctions matches — enhanced due diligence required",
    "Shell company indicators: high-risk jurisdictions, dissolved entities, complex structure",
    "No GLEIF LEI found — entity not registered with Legal Entity Identifier system",
    "3 final rules — regulatory framework hardening",
    "4 proposed rules — more regulation incoming",
    "6 crypto-related bills in Congress — active legislative agenda",
    "2 dissolved/inactive entities — corporate graveyard pattern",
    "2 entities in high-risk offshore jurisdictions",
    "No LEI registration — entity avoids transparency framework"
  ],
  "requiredActions": [
    "International sanctions match — file SAR and escalate to compliance officer",
    "Shell company detected — request beneficial ownership disclosure",
    "Request LEI registration before proceeding"
  ],
  "blockers": []
}

Output fields

| Field | Type | Description |
|---|---|---|
| entity | string | Entity name as submitted |
| compositeScore | number | 0-100 composite risk score (compliance 40% + shell 35% + regulatory velocity 25%) |
| verdict | string | PASS / CONDITIONAL / ENHANCED_DUE_DILIGENCE / FAIL |
| entityCompliance.score | number | Entity Compliance Risk Score 0-100 |
| entityCompliance.ofacHits | number | Count of OFAC SDN list matches |
| entityCompliance.sanctionsHits | number | Count of OpenSanctions matches |
| entityCompliance.shellIndicators | number | Raw shell company signal count (pre-normalization) |
| entityCompliance.riskLevel | string | CLEAR / LOW / MODERATE / HIGH / BLOCKED |
| entityCompliance.signals | string[] | Human-readable compliance signal messages |
| regulatoryVelocity.score | number | Regulatory Velocity Index 0-100 |
| regulatoryVelocity.totalRegulations | number | Total Federal Register results for topic |
| regulatoryVelocity.proposedRules | number | Count of proposed rule documents |
| regulatoryVelocity.finalRules | number | Count of final rule documents |
| regulatoryVelocity.congressBills | number | Count of relevant congressional bills |
| regulatoryVelocity.velocityLevel | string | STATIC / SLOW / MODERATE / FAST / RAPID |
| regulatoryVelocity.signals | string[] | Regulatory signal messages |
| shellDetection.score | number | Shell company probability score 0-100 |
| shellDetection.entityCount | number | Total corporate entities found |
| shellDetection.inactiveEntities | number | Count of dissolved or inactive entities |
| shellDetection.highRiskJurisdictions | number | Count of entities in high-risk offshore jurisdictions |
| shellDetection.leiVerified | boolean | Whether a valid GLEIF LEI was found |
| shellDetection.detectionLevel | string | LEGITIMATE / MINOR_FLAGS / SUSPICIOUS / LIKELY_SHELL / CONFIRMED_SHELL |
| shellDetection.signals | string[] | Shell company signal messages |
| allSignals | string[] | All signals from all three scoring models combined |
| requiredActions | string[] | Compliance actions required based on findings |
| blockers | string[] | Hard blockers that trigger automatic FAIL verdict |

How much does it cost to run crypto compliance checks?

This MCP server uses pay-per-event pricing — you pay $0.045 per tool call. Platform compute costs are included. All 7 tools are priced identically.

| Scenario | Tool calls | Cost per call | Total cost |
|---|---|---|---|
| Quick sanctions check | 1 | $0.045 | $0.045 |
| Single entity full report | 1 | $0.045 | $0.045 |
| Daily counterparty batch (10 entities) | 10 | $0.045 | $0.45 |
| Monthly onboarding pipeline (100 entities) | 100 | $0.045 | $4.50 |
| Enterprise screening (1,000 entities/month) | 1,000 | $0.045 | $45.00 |

You can set a maximum spending limit per run to control costs. The actor stops when your budget is reached and returns a structured error rather than exceeding your limit.

Compare this to Chainalysis KYT at $1,000-10,000/month or Elliptic starting at similar ranges — with this MCP server, a compliance team running 200 screens per month spends under $10 with no subscription commitment. Apify's free tier includes $5 of monthly credits, covering approximately 111 tool calls at no charge.

Using the API directly

Python

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/crypto-compliance-intelligence-mcp").call(run_input={})