Feature/merge validate pipeline

src/sktime_mcp/server.py

@@ -33,7 +33,6 @@
 from mcp.server.stdio import stdio_server
 from mcp.types import TextContent, Tool
 
-from sktime_mcp.composition.validator import get_composition_validator
 from sktime_mcp.config import settings
 from sktime_mcp.tools.classify import (
     fit_predict_classification_tool,
@@ -391,21 +390,6 @@ async def list_tools() -> list[Tool]:
                 "required": ["handle"],
             },
         ),
-        Tool(
-            name="validate_pipeline",
-            description="Check if a pipeline composition is valid",
-            inputSchema={
-                "type": "object",
-                "properties": {
-                    "components": {
-                        "type": "array",
-                        "items": {"type": "string"},
-                        "description": "List of estimator names in pipeline order",
-                    },
-                },
-                "required": ["components"],
-            },
-        ),
         # -- Execution -------------------------------------------------------
         Tool(
             name="fit_predict",
@@ -888,12 +872,6 @@ async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
                 arguments.get("cv_folds", 3),
             )
 
-        elif name == "validate_pipeline":
-            validator = get_composition_validator()
-            validation = validator.validate_pipeline(arguments["components"])
-            result = validation.to_dict()
-            result["success"] = result["valid"]
-
         # -- Data ------------------------------------------------------------
         elif name == "list_available_data":
             result = list_available_data_tool(arguments.get("is_demo"))

tests/test_param_validation.py

@@ -111,6 +111,14 @@ def test_pipeline_unsafe_value_in_params_list(self):
         assert result["success"] is False
         assert "Unsupported type" in result["error"]
 
+    def test_pipeline_composition_check(self):
+        """Invalid pipeline composition (e.g. chaining forecasters) should fail validation."""
+        result = instantiate_pipeline_tool(["NaiveForecaster", "ExponentialSmoothing"])
+        assert result["success"] is False
+        assert "Invalid pipeline composition" in result["error"]
+        assert "validation_errors" in result
+        assert len(result["validation_errors"]) > 0
+
 
 class TestFitPredictValidation:
     """Tests for parameter validation in fit_predict tools."""