diff --git a/superset/mcp_service/chart/schemas.py b/superset/mcp_service/chart/schemas.py
index 1fdb4f43ab6d..0fb1ca1c1e1b 100644
--- a/superset/mcp_service/chart/schemas.py
+++ b/superset/mcp_service/chart/schemas.py
@@ -669,7 +669,10 @@ class ColumnRef(BaseModel):
         ...,
         min_length=1,
         max_length=255,
-        pattern=r"^[a-zA-Z0-9_][a-zA-Z0-9_\s\-\.]*$",
+        # No regex pattern: sanitize_name() already blocks XSS/SQL injection;
+        # many valid column names (digit-prefixed, locale chars, etc.) would
+        # be rejected by a strict pattern while posing no security risk.
+        # Use get_dataset_info to find exact column names.
         validation_alias=AliasChoices("name", "column_name"),
     )
     label: str | None = Field(None, max_length=500)
@@ -743,7 +746,10 @@ class FilterConfig(BaseModel):
         ...,
         min_length=1,
         max_length=255,
-        pattern=r"^[a-zA-Z0-9_][a-zA-Z0-9_\s\-\.]*$",
+        # No regex pattern: sanitize_column() already blocks XSS/SQL injection;
+        # many valid column names (digit-prefixed, locale chars, etc.) would
+        # be rejected by a strict pattern while posing no security risk.
+        # Use get_dataset_info to find exact column names.
         validation_alias=AliasChoices("column", "col"),
     )
     op: Literal[
@@ -775,7 +781,9 @@ def sanitize_column(cls, v: str) -> str:
         """Sanitize filter column name to prevent injection attacks."""
         # sanitize_user_input raises ValueError when allow_empty=False (default)
         # so the return value is guaranteed to be a non-None str
-        return sanitize_user_input(v, "Filter column", max_length=255)  # type: ignore[return-value]
+        return sanitize_user_input(  # type: ignore[return-value]
+            v, "Filter column", max_length=255, check_sql_keywords=True
+        )
 
     @field_validator("value")
     @classmethod
@@ -1082,8 +1090,19 @@ class BigNumberChartConfig(UnknownFieldCheckMixin):
         ),
         min_length=1,
         max_length=255,
-        pattern=r"^[a-zA-Z0-9_][a-zA-Z0-9_\s\-\.]*$",
+        # No regex pattern — see field description above.
     )
+
+    @field_validator("temporal_column")
+    @classmethod
+    def sanitize_temporal_column(cls, v: str | None) -> str | None:
+        """Sanitize temporal column name to prevent XSS and SQL injection."""
+        if v is None:
+            return None
+        return sanitize_user_input(
+            v, "Temporal column", max_length=255, check_sql_keywords=True
+        )
+
     time_grain: TimeGrain | None = Field(
         None,
         description=(
diff --git a/superset/mcp_service/chart/tool/generate_chart.py b/superset/mcp_service/chart/tool/generate_chart.py
index 646ac4d4c2a7..697698bbda03 100644
--- a/superset/mcp_service/chart/tool/generate_chart.py
+++ b/superset/mcp_service/chart/tool/generate_chart.py
@@ -175,7 +175,8 @@ async def generate_chart(  # noqa: C901
     - Set save_chart=True to permanently save the chart
     - LLM clients MUST display returned chart URL to users
     - Use numeric dataset ID or UUID (NOT schema.table_name format)
-    - MUST include chart_type in config (either 'xy' or 'table')
+    - MUST include chart_type in config (one of: 'xy', 'table', 'pie',
+      'big_number', 'pivot_table', 'mixed_timeseries', 'handlebars')
 
     IMPORTANT: The 'chart_type' field in the config is a DISCRIMINATOR that determines
     which chart configuration schema to use. It MUST be included and MUST match the
@@ -200,6 +201,86 @@ async def generate_chart(  # noqa: C901
     }
     ```
 
+
+    Example usage for Pie chart:
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "pie",
+            "dimension": {"name": "product_category"},
+            "metric": {"name": "revenue", "aggregate": "SUM"},
+            "donut": false
+        }
+    }
+    ```
+
+    Example usage for Big Number (no trendline):
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "big_number",
+            "metric": {"name": "total_sales", "aggregate": "SUM"}
+        }
+    }
+    ```
+
+    Example usage for Big Number with trendline:
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "big_number",
+            "metric": {"name": "revenue", "aggregate": "SUM"},
+            "temporal_column": "order_date",
+            "time_grain": "P1M",
+            "show_trendline": true
+        }
+    }
+    ```
+
+    Example usage for Pivot Table:
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "pivot_table",
+            "rows": [{"name": "region"}],
+            "columns": [{"name": "product_category"}],
+            "metrics": [{"name": "revenue", "aggregate": "SUM"}]
+        }
+    }
+    ```
+
+    Example usage for Mixed Timeseries:
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "mixed_timeseries",
+            "x": {"name": "order_date"},
+            "y": [{"name": "revenue", "aggregate": "SUM"}],
+            "primary_kind": "line",
+            "y_secondary": [{"name": "order_count", "aggregate": "COUNT"}],
+            "secondary_kind": "bar"
+        }
+    }
+    ```
+
+    Example usage for Handlebars:
+    ```json
+    {
+        "dataset_id": 123,
+        "config": {
+            "chart_type": "handlebars",
+            "handlebars_template": "{{#each data}}{{this.name}}{{/each}}",
+            "groupby": [{"name": "product"}],
+            "metrics": [{"name": "revenue", "aggregate": "SUM"}]
+        }
+    }
+    ```
+
     Example usage for Table chart:
     ```json
     {
diff --git a/superset/mcp_service/chart/validation/schema_validator.py b/superset/mcp_service/chart/validation/schema_validator.py
index 7cae450ff599..8ae2b2aad86a 100644
--- a/superset/mcp_service/chart/validation/schema_validator.py
+++ b/superset/mcp_service/chart/validation/schema_validator.py
@@ -525,6 +525,37 @@ def _pre_validate_mixed_timeseries_config(
 
         return True, None
 
+    @staticmethod
+    def _format_single_error(err: Dict[str, Any]) -> tuple[str, str]:
+        """Return (detail_message, optional_suggestion) for one pydantic error."""
+        loc_parts = [str(p) for p in err.get("loc", [])]
+        loc = " -> ".join(loc_parts)
+        msg = err.get("msg", "Validation failed")
+        err_type = err.get("type", "")
+        field = loc_parts[-1] if loc_parts else "field"
+
+        if err_type == "string_pattern_mismatch":
+            return (
+                f"'{field}' value does not match the required pattern. "
+                "Use the exact value from your dataset.",
+                "Use get_dataset_info to find exact column names and values",
+            )
+        if err_type == "literal_error":
+            # Preserve the pydantic message ("Input should be ...") which is
+            # already human-readable; just prefix with the field name for context.
+            return f"'{field}': {msg}", ""
+        if err_type == "missing":
+            return (
+                f"Required field '{field}' is missing",
+                "Check the chart_type examples in the tool description",
+            )
+        if err_type == "value_error":
+            return (
+                f"{loc}: {msg}",
+                "Use get_dataset_info to verify column names and types",
+            )
+        return f"{loc}: {msg}", ""
+
     @staticmethod
     def _enhance_validation_error(
         error: PydanticValidationError, request_data: Dict[str, Any]
@@ -609,22 +640,29 @@ def _enhance_validation_error(
                         error_code="BIG_NUMBER_VALIDATION_ERROR",
                     )
 
-        # Default enhanced error
+        # Default enhanced error: build actionable per-field messages
         error_details = []
-        for err in errors[:3]:  # Show first 3 errors
-            loc = " -> ".join(str(location) for location in err.get("loc", []))
-            msg = err.get("msg", "Validation failed")
-            error_details.append(f"{loc}: {msg}")
+        extra_suggestions: list[str] = []
+        for err in errors[:5]:  # Surface up to 5 errors
+            detail, suggestion = SchemaValidator._format_single_error(err)
+            error_details.append(detail)
+            if suggestion:
+                extra_suggestions.append(suggestion)
 
         return ChartGenerationError(
             error_type="validation_error",
             message="Chart configuration validation failed",
             details="; ".join(error_details),
-            suggestions=[
-                "Check that all required fields are present",
-                "Ensure field types match the schema",
-                "Use get_dataset_info to verify column names",
-                "Refer to the API documentation for field requirements",
-            ],
+            suggestions=list(
+                dict.fromkeys(
+                    [
+                        "Check that all required fields are present",
+                        "Ensure field types match the schema",
+                        "Use get_dataset_info to verify column names",
+                        "Refer to the API documentation for field requirements",
+                    ]
+                    + extra_suggestions
+                )
+            ),
             error_code="VALIDATION_ERROR",
         )
diff --git a/tests/unit_tests/mcp_service/chart/test_chart_schemas.py b/tests/unit_tests/mcp_service/chart/test_chart_schemas.py
index 1da9d1bc3a74..a401a6f47eb8 100644
--- a/tests/unit_tests/mcp_service/chart/test_chart_schemas.py
+++ b/tests/unit_tests/mcp_service/chart/test_chart_schemas.py
@@ -778,3 +778,104 @@ def test_client_warnings_discarded_even_when_server_also_warns(self) -> None:
         assert len(req.sanitization_warnings) == 1
         assert "chart_name" in req.sanitization_warnings[0]
         assert "injected" not in req.sanitization_warnings[0]
+
+
+class TestColumnRefNameRelaxedPattern:
+    """ColumnRef.name no longer enforces a strict regex pattern.
+
+    Many valid database column names were previously rejected:
+    - Names starting with a digit (e.g. "1Q_revenue")
+    - Names with locale-specific characters
+    The field_validator sanitize_name() still blocks XSS and SQL injection.
+    """
+
+    def test_digit_prefixed_name_accepted(self) -> None:
+        """Column names starting with a digit must now be accepted."""
+        col = ColumnRef(name="1Q_revenue")
+        assert col.name == "1Q_revenue"
+
+    def test_name_with_hyphen_accepted(self) -> None:
+        col = ColumnRef(name="order-date")
+        assert col.name == "order-date"
+
+    def test_name_with_dot_accepted(self) -> None:
+        col = ColumnRef(name="schema.column")
+        assert col.name == "schema.column"
+
+    def test_name_with_spaces_accepted(self) -> None:
+        col = ColumnRef(name="Total Revenue")
+        assert col.name == "Total Revenue"
+
+    def test_script_tag_neutralized(self) -> None:
+        """sanitize_name() neutralizes script-tag XSS via nh3.
+        Depending on nh3 version, nh3 either strips the entire script element
+        including its content (leaving empty → ValidationError) or strips only
+        the tag delimiters (leaving 'alert(1)'). Either way, no raw <script>
+        tag is stored in the column name."""
+        try:
+            col = ColumnRef(name="<script>alert(1)</script>")
+            assert "<script>" not in col.name
+        except ValidationError:
+            pass  # nh3 stripped entire element; empty-value guard raised
+
+    def test_event_handler_injection_blocked(self) -> None:
+        """sanitize_name() rejects event-handler injection patterns (on...=)."""
+        with pytest.raises(ValidationError):
+            ColumnRef(name="col onclick=alert(1)")
+
+    def test_sql_keyword_blocked(self) -> None:
+        """check_sql_keywords=True still blocks pure SQL statements."""
+        with pytest.raises(ValidationError):
+            ColumnRef(name="1; DROP TABLE users; --")
+
+    def test_empty_name_blocked(self) -> None:
+        with pytest.raises(ValidationError):
+            ColumnRef(name="")
+
+    def test_table_chart_with_digit_prefixed_column(self) -> None:
+        """End-to-end: digit-prefixed column passes through GenerateChartRequest."""
+        req = GenerateChartRequest(
+            dataset_id=1,
+            config={
+                "chart_type": "table",
+                "columns": [
+                    {"name": "1Q_revenue"},
+                    {"name": "product_name"},
+                ],
+            },
+        )
+        assert req.config.chart_type == "table"
+
+    def test_xy_chart_with_hyphenated_column(self) -> None:
+        req = GenerateChartRequest(
+            dataset_id=1,
+            config={
+                "chart_type": "xy",
+                "x": {"name": "order-date"},
+                "y": [{"name": "1Q-revenue", "aggregate": "SUM"}],
+            },
+        )
+        assert req.config.chart_type == "xy"
+
+
+class TestFilterConfigColumnRelaxedPattern:
+    """FilterConfig.column no longer enforces a strict regex pattern."""
+
+    def test_digit_prefixed_filter_column_accepted(self) -> None:
+        from superset.mcp_service.chart.schemas import FilterConfig
+
+        f = FilterConfig(column="1Q_flag", op="=", value="active")
+        assert f.column == "1Q_flag"
+
+    def test_hyphenated_filter_column_accepted(self) -> None:
+        from superset.mcp_service.chart.schemas import FilterConfig
+
+        f = FilterConfig(column="order-status", op="=", value="shipped")
+        assert f.column == "order-status"
+
+    def test_sql_injection_in_filter_column_blocked(self) -> None:
+        """FilterConfig.sanitize_column uses check_sql_keywords=True."""
+        from superset.mcp_service.chart.schemas import FilterConfig
+
+        with pytest.raises(ValidationError):
+            FilterConfig(column="col; DROP TABLE users; --", op="=", value="x")