Engineered data lakes for autonomous AI agents.
Columnar Speed. Cryptographic Provenance. Zero Hallucinations.

-- High-priority vulnerability intelligence query via DuckDB
SELECT cve_id, vendor, product, date_added, ransomware_use, required_action
FROM 'foundry://cybersecurity/cisa_kev/*.parquet'
WHERE ransomware_use = 'Known'
  AND date_added >= '2024-01-01'
ORDER BY date_added DESC
LIMIT 10;

{
  "jsonrpc": "2.0",
  "id": "agent-step-402",
  "method": "tools/call",
  "params": {
    "name": "query_dataset",
    "arguments": {
      "dataset": "cisa_kev",
      "limit": 5
    }
  }
}

// WORKFLOW A: SEC Research & Filing Cadence Analysis
// User Prompt: "Find recent filing activity for Apple Inc. (AAPL) and summarize important patterns."

// 1. Tool Call: query_dataset(dataset="sec_company_tickers", limit=1)
// Result: CIK "0000320193", Ticker "AAPL", Title "Apple Inc."

// 2. Tool Call: query_dataset(dataset="sec_filing_index", limit=5)
// Verified Response from 9.5M+ EDGAR Partition Lake:
{
  "company_name": "Apple Inc.",
  "cik": "0000320193",
  "recent_filings": [
    { "form": "10-K", "date": "2025-10-31", "accession": "0000320193-25-000106" },
    { "form": "8-K",  "date": "2025-10-31", "accession": "0000320193-25-000108" },
    { "form": "4",    "date": "2025-10-15", "accession": "0000320193-25-000101" }
  ],
  "provenance_receipt": "rcpt_0rwy6v91k8a0m2n4",
  "sha256_digest": "sha256:d8b248a31e1c3905e461b2a259c687f82b72c91834167e4125b6ecf22a5598fa"
}

// WORKFLOW B: Cybersecurity — KEV vs. EPSS Exploitation Matrix
// User Prompt: "Compare known exploited vulnerabilities with exploitation probability data."

// 1. Tool Call: query_dataset(dataset="cisa_kev", limit=2)
// Verified Record: CVE-2021-27104 (Accellion FTA OS Command Injection)
// Ransomware Use: "Known" | Required Action: "Apply updates per vendor instructions."

// 2. Tool Call: query_dataset(dataset="epss_scores", limit=2)
// Cross-Referenced Exploit Probability Score:
{
  "cve_id": "CVE-2021-27104",
  "vendor": "Accellion",
  "product": "FTA",
  "ransomware_campaign": true,
  "epss_percentile": 0.9748,
  "remediation_status": "URGENT",
  "provenance_receipt": "rcpt_0rwy702b8x991kc2",
  "sha256_digest": "sha256:7c91a45b98ef1134e12cbb41a02798e162f559c8d103b418a901ee19842f1b0a"
}

// WORKFLOW C: Crypto Research — Stablecoin Supply Trends & Peg Stability
// User Prompt: "Analyze available stablecoin supply trends and peg stability using ELYRAON's datasets."

// 1. Tool Call: query_dataset(dataset="stablecoin_market_snapshots", limit=2)
// 2. Tool Call: query_dataset(dataset="stablecoin_supply_daily", limit=2)
// Verified Live Response:
{
  "symbol": "USDT",
  "name": "Tether",
  "price_usd": 0.999778,
  "market_cap_usd": 183434443781.99,
  "volume_24h_usd": 71884732560.81,
  "depeg_bps": -2,
  "peg_status": "NORMAL_BOUNDS",
  "provenance_receipt": "rcpt_0rwy7189x011za79",
  "sha256_digest": "sha256:1a84f3c0598711e4d0b168925bb084920e402891d4e156291a5e197c39029bfb"
}

import os
import httpx

client = httpx.Client(
    base_url="https://mcp.elyraon.com.co",
    headers={"Authorization": f"Bearer {os.environ['ELYREON_API_KEY']}"}
)

# Execute tool call over Model Context Protocol
response = client.post("/mcp", json={
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "query_dataset",
        "arguments": {"dataset": "sec_company_tickers", "limit": 10}
    }
})

data = response.json()["result"]["structuredContent"]["data"]
print(f"Retrieved {len(data['rows'])} tickers with verified receipt: {response.json()['result']['structuredContent']['meta']['receipt']['receipt_id']}")

curl -X POST https://mcp.elyraon.com.co/mcp \
  -H "Authorization: Bearer $ELYREON_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "query_dataset",
      "arguments": {
        "dataset": "openfda_drug_labels",
        "limit": 3
      }
    }
  }'