superset2/superset/mcp_service/dataset/tool/list_datasets.py

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"""
List datasets FastMCP tool (Advanced with metadata cache control)

This module contains the FastMCP tool for listing datasets using
advanced filtering with clear, unambiguous request schema and metadata cache control.
"""

import logging
from typing import TYPE_CHECKING

from fastmcp import Context
from superset_core.mcp import tool

if TYPE_CHECKING:
    from superset.connectors.sqla.models import SqlaTable

from superset.mcp_service.dataset.schemas import (
    DatasetFilter,
    DatasetInfo,
    DatasetList,
    ListDatasetsRequest,
    serialize_dataset_object,
)
from superset.mcp_service.mcp_core import ModelListCore
from superset.mcp_service.utils.schema_utils import parse_request

logger = logging.getLogger(__name__)

DEFAULT_DATASET_COLUMNS = [
    "id",
    "table_name",
    "schema",
    "uuid",
    "database_name",
    "changed_by_name",
    "changed_on",
    "created_by_name",
    "created_on",
    "metrics",
    "columns",
]

SORTABLE_DATASET_COLUMNS = [
    "id",
    "table_name",
    "schema",
    "changed_on",
    "created_on",
]


@tool(tags=["core"])
@parse_request(ListDatasetsRequest)
async def list_datasets(request: ListDatasetsRequest, ctx: Context) -> DatasetList:
    """List datasets with filtering and search.

    Returns dataset metadata including columns and metrics.

    Sortable columns for order_column: id, table_name, schema, changed_on,
    created_on
    """
    await ctx.info(
        "Listing datasets: page=%s, page_size=%s, search=%s"
        % (
            request.page,
            request.page_size,
            request.search,
        )
    )
    await ctx.debug(
        "Dataset listing parameters: filters=%s, order_column=%s, "
        "order_direction=%s, select_columns=%s"
        % (
            request.filters,
            request.order_column,
            request.order_direction,
            request.select_columns,
        )
    )
    await ctx.debug(
        "Metadata cache settings: use_cache=%s, refresh_metadata=%s, force_refresh=%s"
        % (
            request.use_cache,
            request.refresh_metadata,
            request.force_refresh,
        )
    )

    try:
        from superset.daos.dataset import DatasetDAO

        def _serialize_dataset(
            obj: "SqlaTable | None", cols: list[str] | None
        ) -> DatasetInfo | None:
            """Serialize dataset (filtering via model_serializer)."""
            return serialize_dataset_object(obj)

        # Create tool with standard serialization
        tool = ModelListCore(
            dao_class=DatasetDAO,
            output_schema=DatasetInfo,
            item_serializer=_serialize_dataset,
            filter_type=DatasetFilter,
            default_columns=DEFAULT_DATASET_COLUMNS,
            search_columns=["schema", "sql", "table_name", "uuid"],
            list_field_name="datasets",
            output_list_schema=DatasetList,
            logger=logger,
        )

        result = tool.run_tool(
            filters=request.filters,
            search=request.search,
            select_columns=request.select_columns,
            order_column=request.order_column,
            order_direction=request.order_direction,
            page=max(request.page - 1, 0),
            page_size=request.page_size,
        )

        await ctx.info(
            "Datasets listed successfully: count=%s, total_count=%s, total_pages=%s"
            % (
                len(result.datasets) if hasattr(result, "datasets") else 0,
                getattr(result, "total_count", None),
                getattr(result, "total_pages", None),
            )
        )

        # Apply field filtering via serialization context if select_columns specified
        # This triggers DatasetInfo._filter_fields_by_context for each dataset
        if request.select_columns:
            await ctx.debug(
                "Applying field filtering via serialization context: select_columns=%s"
                % (request.select_columns,)
            )
            # Return dict with context - FastMCP will serialize it
            return result.model_dump(
                mode="json", context={"select_columns": request.select_columns}
            )

        # No filtering - return full result as dict
        return result.model_dump(mode="json")

    except Exception as e:
        await ctx.error(
            "Dataset listing failed: page=%s, page_size=%s, error=%s, error_type=%s"
            % (
                request.page,
                request.page_size,
                str(e),
                type(e).__name__,
            )
        )
        raise