feat(mcp): tool search_organisations (résolution nom -> id)

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

src/mcp/queries.py

@@ -0,0 +1,37 @@
+# src/mcp/queries.py
+import re
+
+from src.mcp.serialization import (
+    to_json_records,  # noqa: F401 (utilisé aux tâches suivantes)
+)
+from src.utils.data import DF_ACHETEURS, DF_TITULAIRES
+from src.utils.search import search_org
+
+PAGE_SIZE = 50
+TOP_N = 10
+ORG_FRAMES = {"acheteur": DF_ACHETEURS, "titulaire": DF_TITULAIRES}
+
+
+def _extract_plain_text(html_str: str) -> str:
+    """Extract plain text from HTML link, e.g. '<a...>123</a>' -> '123'."""
+    match = re.search(r">([^<]+)<", html_str)
+    return match.group(1) if match else html_str
+
+
+def search_organisations(
+    query: str, org_type: str = "acheteur", limite: int = 20
+) -> list[dict]:
+    """Recherche des organisations par nom, résout un nom -> id."""
+    if org_type not in ORG_FRAMES:
+        raise ValueError(
+            f"type invalide: {org_type!r} (attendu 'acheteur' ou 'titulaire')"
+        )
+    df = search_org(ORG_FRAMES[org_type], query, org_type, track=False).head(limite)
+    return [
+        {
+            "id": _extract_plain_text(r[f"{org_type}_id"]),
+            "nom": _extract_plain_text(r[f"{org_type}_nom"]),
+            "departement": r.get("Département"),
+        }
+        for r in df.to_dicts()
+    ]