diff --git a/src/sktime_mcp/tools/codegen.py b/src/sktime_mcp/tools/codegen.py
index e68a6df6..0320d35f 100644
--- a/src/sktime_mcp/tools/codegen.py
+++ b/src/sktime_mcp/tools/codegen.py
@@ -4,6 +4,7 @@
 Generates Python code to recreate estimators and pipelines.
 """
 
+import inspect
 import keyword
 from typing import Any
 
@@ -51,6 +52,21 @@ def _is_valid_var_name(var_name: str) -> bool:
     return isinstance(var_name, str) and var_name.isidentifier() and not keyword.iskeyword(var_name)
 
 
+def _supports_forecasting_fit_example(dataset: str) -> bool:
+    """Return whether a demo dataset is compatible with the forecasting example template."""
+    module_path = DEMO_DATASETS.get(dataset)
+    if module_path is None:
+        return False
+
+    module_parts = module_path.rsplit(".", 1)
+    module = __import__(module_parts[0], fromlist=[module_parts[1]])
+    loader = getattr(module, module_parts[1])
+    signature = inspect.signature(loader)
+
+    # Supervised/classification/regression demo loaders typically expose return_X_y.
+    return "return_X_y" not in signature.parameters
+
+
 def _generate_single_estimator_code(
     estimator_name: str, params: dict[str, Any], var_name: str = "model"
 ) -> dict[str, Any]:
@@ -254,7 +270,23 @@ def export_code_tool(
     # Optionally add fit/predict example
     if include_fit_example:
         # Resolve the dataset loader from DEMO_DATASETS
-        if dataset and dataset in DEMO_DATASETS:
+        if dataset and dataset not in DEMO_DATASETS:
+            return {
+                "success": False,
+                "error": f"Unknown dataset: {dataset}",
+                "available": sorted(DEMO_DATASETS.keys()),
+            }
+
+        if dataset and not _supports_forecasting_fit_example(dataset):
+            return {
+                "success": False,
+                "error": (
+                    f"Dataset '{dataset}' is not supported for forecasting fit examples. "
+                    "Please use a forecasting-compatible demo dataset such as 'airline'."
+                ),
+            }
+
+        if dataset:
             module_path = DEMO_DATASETS[dataset]
             module_parts = module_path.rsplit(".", 1)
             loader_module = module_parts[0]
diff --git a/tests/test_codegen.py b/tests/test_codegen.py
index 95e9a71e..9e5fcd8a 100644
--- a/tests/test_codegen.py
+++ b/tests/test_codegen.py
@@ -242,6 +242,26 @@ def test_include_fit_example_false(self):
         finally:
             self._cleanup_handle(handle)
 
+    def test_include_fit_example_supported_dataset(self):
+        """Supported forecasting demo datasets should still produce example code."""
+        handle = self._create_handle()
+        try:
+            result = export_code_tool(handle, include_fit_example=True, dataset="airline")
+            assert result["success"]
+            assert "load_airline" in result["code"]
+        finally:
+            self._cleanup_handle(handle)
+
+    def test_include_fit_example_rejects_unsupported_demo_dataset(self):
+        """Supervised demo datasets should be rejected for forecasting example generation."""
+        handle = self._create_handle()
+        try:
+            result = export_code_tool(handle, include_fit_example=True, dataset="basic_motions")
+            assert result["success"] is False
+            assert "not supported for forecasting fit examples" in result["error"]
+        finally:
+            self._cleanup_handle(handle)
+
     def test_custom_var_name(self):
         """Custom var_name should appear in the generated code."""
         handle = self._create_handle()