diff --git a/tradingagents/dataflows/discovery/scanners/__init__.py b/tradingagents/dataflows/discovery/scanners/__init__.py
index 0ca0c4dd..c799a1cf 100644
--- a/tradingagents/dataflows/discovery/scanners/__init__.py
+++ b/tradingagents/dataflows/discovery/scanners/__init__.py
@@ -3,6 +3,7 @@
 # Import all scanners to trigger registration
 from . import (
     analyst_upgrades,  # noqa: F401
+    dark_pool_flow,  # noqa: F401
     earnings_beat,  # noqa: F401
     earnings_calendar,  # noqa: F401
     high_52w_breakout,  # noqa: F401
diff --git a/tradingagents/dataflows/discovery/scanners/dark_pool_flow.py b/tradingagents/dataflows/discovery/scanners/dark_pool_flow.py
new file mode 100644
index 00000000..67df36bc
--- /dev/null
+++ b/tradingagents/dataflows/discovery/scanners/dark_pool_flow.py
@@ -0,0 +1,164 @@
+"""Dark pool flow scanner — scrapes FINRA ATS anomalies from meridianfin.io."""
+
+from typing import Any, Dict, List
+
+from tradingagents.dataflows.discovery.scanner_registry import SCANNER_REGISTRY, BaseScanner
+from tradingagents.dataflows.discovery.utils import Priority
+from tradingagents.utils.logger import get_logger
+
+logger = get_logger(__name__)
+
+_SOURCE_URL = "https://meridianfin.io/darkpool"
+
+
+def _parse_volume(text: str) -> int:
+    """Parse volume strings like '60.64M', '1.2B', '500K' into integers."""
+    import re
+
+    text = text.strip().upper().replace(",", "")
+    match = re.match(r"([\d.]+)\s*([KMBT]?)", text)
+    if not match:
+        return 0
+    value = float(match.group(1))
+    suffix = match.group(2)
+    multipliers = {"K": 1_000, "M": 1_000_000, "B": 1_000_000_000, "T": 1_000_000_000_000}
+    return int(value * multipliers.get(suffix, 1))
+
+
+class DarkPoolFlowScanner(BaseScanner):
+    """Scan for unusual off-exchange (dark pool) volume anomalies.
+
+    Data source: meridianfin.io — daily FINRA ATS data with Z-score anomaly
+    detection pre-computed. 1-day lag (FINRA settlement). No auth required.
+    """
+
+    name = "dark_pool_flow"
+    pipeline = "edge"
+    strategy = "institutional_accumulation"
+
+    def __init__(self, config: Dict[str, Any]):
+        super().__init__(config)
+        self.min_z_score = self.scanner_config.get("min_z_score", 2.0)
+        self.min_dark_pool_pct = self.scanner_config.get("min_dark_pool_pct", 40.0)
+        self.source_url = self.scanner_config.get("source_url", _SOURCE_URL)
+
+    def scan(self, state: Dict[str, Any]) -> List[Dict[str, Any]]:
+        if not self.is_enabled():
+            return []
+
+        logger.info("🌑 Scanning dark pool flow anomalies (meridianfin.io)...")
+
+        try:
+            rows = self._fetch_anomalies()
+        except Exception as e:
+            logger.warning(f"⚠️  Dark pool flow scrape failed: {e}")
+            return []
+
+        if not rows:
+            logger.info("Found 0 dark pool anomalies")
+            return []
+
+        candidates = []
+        for row in rows:
+            z = row.get("z_score", 0.0)
+            dp_pct = row.get("dark_pool_pct", 0.0)
+
+            if z < self.min_z_score or dp_pct < self.min_dark_pool_pct:
+                continue
+
+            if z >= 4.0:
+                priority = Priority.CRITICAL.value
+            elif z >= 3.0:
+                priority = Priority.HIGH.value
+            else:
+                priority = Priority.MEDIUM.value
+
+            vol = row.get("off_exchange_vol", 0)
+            candidates.append(
+                {
+                    "ticker": row["ticker"],
+                    "source": self.name,
+                    "context": (
+                        f"Dark pool anomaly: {dp_pct:.1f}% off-exchange"
+                        f" | Z-score {z:.2f}"
+                        f" | Vol: {vol:,}"
+                    ),
+                    "priority": priority,
+                    "strategy": self.strategy,
+                    "dark_pool_pct": dp_pct,
+                    "z_score": z,
+                    "off_exchange_vol": vol,
+                }
+            )
+
+        candidates = candidates[: self.limit]
+        logger.info(f"Found {len(candidates)} dark pool anomalies")
+        return candidates
+
+    def _fetch_anomalies(self) -> List[Dict[str, Any]]:
+        """Scrape the anomaly table from meridianfin.io/darkpool."""
+        import re
+
+        import requests
+        from bs4 import BeautifulSoup
+
+        # re is used for ticker validation below
+
+        headers = {
+            "User-Agent": (
+                "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+                "AppleWebKit/537.36 (KHTML, like Gecko) "
+                "Chrome/123.0.0.0 Safari/537.36"
+            ),
+            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+            "Accept-Language": "en-US,en;q=0.5",
+        }
+
+        resp = requests.get(self.source_url, headers=headers, timeout=15)
+        resp.raise_for_status()
+
+        soup = BeautifulSoup(resp.text, "html.parser")
+
+        # Find the anomaly table — look for a <table> containing ticker-like cells
+        table = soup.find("table")
+        if not table:
+            logger.warning("No <table> found on meridianfin.io/darkpool")
+            return []
+
+        rows = []
+        tbody = table.find("tbody") or table
+        for tr in tbody.find_all("tr"):
+            cells = [td.get_text(strip=True) for td in tr.find_all(["td", "th"])]
+            if len(cells) < 4:
+                continue
+
+            # Skip header rows
+            if cells[0].lower() in ("ticker", "symbol", "#", ""):
+                continue
+
+            ticker = cells[0].upper()
+            # Validate ticker format (1-5 uppercase letters)
+            if not re.match(r"^[A-Z]{1,5}$", ticker):
+                continue
+
+            # Columns: Ticker | Volume | DPI (%) | Z-Score | Date | Company | OTC % | Source
+            try:
+                off_exchange_vol = _parse_volume(cells[1])
+                dark_pool_pct = float(re.sub(r"[%,]", "", cells[2]))
+                z_score = float(cells[3])
+            except (IndexError, ValueError):
+                continue
+
+            rows.append(
+                {
+                    "ticker": ticker,
+                    "off_exchange_vol": off_exchange_vol,
+                    "dark_pool_pct": dark_pool_pct,
+                    "z_score": z_score,
+                }
+            )
+
+        return rows
+
+
+SCANNER_REGISTRY.register(DarkPoolFlowScanner)
diff --git a/tradingagents/default_config.py b/tradingagents/default_config.py
index 5ee9325c..053e07db 100644
--- a/tradingagents/default_config.py
+++ b/tradingagents/default_config.py
@@ -134,6 +134,14 @@ DEFAULT_CONFIG = {
         # ========================================
         "scanners": {
             # Edge signals - Early information advantages
+            "dark_pool_flow": {
+                "enabled": True,
+                "pipeline": "edge",
+                "limit": 8,
+                "min_z_score": 2.0,         # Minimum FINRA ATS anomaly Z-score
+                "min_dark_pool_pct": 40.0,  # Minimum % of daily volume off-exchange
+                "source_url": "https://meridianfin.io/darkpool",
+            },
             "insider_buying": {
                 "enabled": True,
                 "pipeline": "edge",