fix: support Qdrant backend on non-AVX CPUs

- doctor: skip LanceDB check when qdrant_storage/ dir detected
- topology: use daemon socket instead of local store (avoids lancedb crash)
- qdrant_store: add records_as_dataframe() + wire into _TableShim
  so build_runtime_graph() works with Qdrant (was returning empty)

src/iai_mcp/cli.py

@@ -1499,14 +1499,31 @@ def cmd_topology(args: argparse.Namespace) -> int:
     guard). The CLI is a print-only command -- no event writes,
     no state mutation. compute_and_emit() runs in S4's offline pass instead
     (see `iai_mcp.s4.run_offline_pass`).
-    """
-    from iai_mcp.retrieve import build_runtime_graph
-    from iai_mcp.sigma import compute_topology_snapshot
-    from iai_mcp.store import MemoryStore
 
-    store = MemoryStore()
-    graph, _assignment, _rich_club = build_runtime_graph(store)
-    snap = compute_topology_snapshot(graph)
+    Uses the daemon's topology handler via the control socket so the CLI
+    never needs to instantiate a local store (avoids lancedb/Qdrant deps
+    on non-AVX CPUs or when QDRANT_URL is only in systemd env).
+    """
+    snap = _send_socket_request({"type": "topology"})
+    if snap is None:
+        print("ERROR: daemon unreachable", file=sys.stderr)
+        return 1
+
+    def _fmt(v) -> str:
+        if v is None:
+            return "insufficient_data"
+        if isinstance(v, float):
+            return f"{v:.4f}"
+        return str(v)
+
+    print(f"C: {_fmt(snap.get('C'))}")
+    print(f"L: {_fmt(snap.get('L'))}")
+    print(f"sigma: {_fmt(snap.get('sigma'))}")
+    print(f"communities: {_fmt(snap.get('community_count'))}")
+    print(f"rich_club_ratio: {_fmt(snap.get('rich_club_ratio'))}")
+    print(f"N: {_fmt(snap.get('N'))}")
+    print(f"regime: {_fmt(snap.get('regime'))}")
+    return 0
 
     def _fmt(v) -> str:
         if v is None:

src/iai_mcp/doctor.py

@@ -433,7 +433,31 @@ def check_f_lancedb_readable() -> CheckResult:
     Open a MemoryStore handle. The constructor opens the lancedb connection;
     if the directory is corrupt / permission-denied / disk-full, the
     constructor raises and we report FAIL.
+
+    Skips gracefully when Qdrant is the active backend or lancedb is
+    unavailable (non-AVX CPU, etc.) — returns PASS with skip reason.
     """
+    from iai_mcp.store import _use_qdrant
+
+    if _use_qdrant():
+        return CheckResult(
+            "(f) lancedb store readable",
+            True,
+            "skipped (Qdrant backend active)",
+        )
+
+    # Heuristic: qdrant_storage/ directory present → Qdrant is the active
+    # backend even if QDRANT_URL is not set in the current shell (e.g.
+    # systemd service provides it but interactive shell does not).
+    env_path = os.environ.get("IAI_MCP_STORE")
+    store_root = Path(env_path) if env_path else (Path.home() / ".iai-mcp")
+    if (store_root / "qdrant_storage").exists():
+        return CheckResult(
+            "(f) lancedb store readable",
+            True,
+            "skipped (Qdrant backend detected via qdrant_storage/)",
+        )
+
     try:
         from iai_mcp.store import MemoryStore
 
@@ -443,11 +467,24 @@ def check_f_lancedb_readable() -> CheckResult:
             True,
             "opens without error",
         )
+    except KeyboardInterrupt:
+        raise
+    except SystemExit:
+        raise
     except Exception as e:  # noqa: BLE001 — surface any open failure
+        # Non-AVX CPUs may crash in lancedb native libs (SIGILL); treat as
+        # unavailable rather than a store corruption failure.
+        exc_name = type(e).__name__
+        if exc_name == "IllegalInstruction" or "illegal" in str(e).lower():
+            return CheckResult(
+                "(f) lancedb store readable",
+                True,
+                f"skipped (lancedb unavailable on this CPU: {exc_name})",
+            )
         return CheckResult(
             "(f) lancedb store readable",
             False,
-            f"open failed: {type(e).__name__}: {e}",
+            f"open failed: {exc_name}: {e}",
         )
 
 

src/iai_mcp/qdrant_store.py

@@ -1289,6 +1289,52 @@ class QdrantStore:
         except Exception:
             return pd.DataFrame(columns=["src", "dst", "edge_type", "weight", "updated_at"])
 
+    def records_as_dataframe(self) -> "pd.DataFrame":
+        """Return all records from the records collection as a pandas DataFrame."""
+        try:
+            records = self.all_records()
+            if not records:
+                return pd.DataFrame(columns=[
+                    "id", "tier", "literal_surface", "embedding",
+                    "community_id", "centrality", "pinned",
+                    "tags_json", "language", "aaak_index",
+                    "stability", "difficulty", "last_reviewed",
+                    "never_decay", "never_merge", "detail_level",
+                    "s5_trust_score", "structure_hv",
+                ])
+            rows = []
+            for r in records:
+                rows.append({
+                    "id": str(r.id),
+                    "tier": r.tier,
+                    "literal_surface": r.literal_surface,
+                    "embedding": r.embedding,
+                    "community_id": str(r.community_id) if r.community_id else None,
+                    "centrality": r.centrality,
+                    "pinned": r.pinned,
+                    "tags_json": r.tags_json if hasattr(r, "tags_json") else "[]",
+                    "language": r.language,
+                    "aaak_index": r.aaak_index,
+                    "stability": r.stability,
+                    "difficulty": r.difficulty,
+                    "last_reviewed": str(r.last_reviewed) if r.last_reviewed else None,
+                    "never_decay": r.never_decay,
+                    "never_merge": r.never_merge,
+                    "detail_level": r.detail_level,
+                    "s5_trust_score": r.s5_trust_score,
+                    "structure_hv": r.structure_hv.hex() if r.structure_hv else "",
+                })
+            return pd.DataFrame(rows)
+        except Exception:
+            return pd.DataFrame(columns=[
+                "id", "tier", "literal_surface", "embedding",
+                "community_id", "centrality", "pinned",
+                "tags_json", "language", "aaak_index",
+                "stability", "difficulty", "last_reviewed",
+                "never_decay", "never_merge", "detail_level",
+                "s5_trust_score", "structure_hv",
+            ])
+
   # ------------------------------------------------------------------ db shim
 
     class _DbShim:
@@ -1311,6 +1357,8 @@ class QdrantStore:
             def to_pandas(self) -> pd.DataFrame:
                 if self._name == EDGES_TABLE:
                     return self._store.edges_as_dataframe()
+                elif self._name == RECORDS_TABLE:
+                    return self._store.records_as_dataframe()
                 elif self._name == EVENTS_TABLE:
                     return pd.DataFrame()
                 return pd.DataFrame()