Create graph_metrics.py

mcp/graph_metrics.py

@@ -0,0 +1,31 @@
+# mcp/graph_metrics.py
+"""
+Basic graph-analytics helpers (pure CPU, no heavy maths):
+  • build_nx  – convert agraph nodes/edges → NetworkX graph
+  • get_top_hubs – return top-k nodes by degree-centrality
+  • get_density – overall graph density
+"""
+
+from typing import List, Dict, Tuple
+import networkx as nx
+
+# ----------------------------------------------------------------------
+def build_nx(nodes: List[Dict], edges: List[Dict]) -> nx.Graph:
+    G = nx.Graph()
+    for n in nodes:
+        G.add_node(n["id"], label=n.get("label", n["id"]))
+    for e in edges:
+        G.add_edge(e["source"], e["target"])
+    return G
+
+
+def get_top_hubs(G: nx.Graph, k: int = 5) -> List[Tuple[str, float]]:
+    """
+    Return [(node_id, centrality)] sorted desc.
+    """
+    dc = nx.degree_centrality(G)
+    return sorted(dc.items(), key=lambda x: x[1], reverse=True)[:k]
+
+
+def get_density(G: nx.Graph) -> float:
+    return nx.density(G)