query_metrics
Query the dbt Semantic Layer to analyze business data by grouping, ordering, and filtering metrics, dimensions, and entities for precise insights.
Instructions
This tool allows ordering and grouping by dimensions and entities. To use this tool, you must first know about specific metrics, dimensions and entities to provide. You can call the list_metrics, get_dimensions, and get_entities tools to get information about which metrics, dimensions, and entities to use.
When using the order_by parameter, you must ensure that the dimension or
entity also appears in the group_by parameter. When fulfilling a lookback
query, prefer using order_by and limit instead of using the where parameter.
A lookback query requires that the order_by parameter includes a descending
order for a time dimension.
The where parameter should be database agnostic SQL syntax, however dimensions
and entity are referenced differently. For categorical dimensions,
use {{ Dimension('<name>') }} and for time dimensions add the grain
like {{ TimeDimension('<name>', '<grain>') }}. For entities,
use {{ Entity('<name>') }}. When referencing dates in the where
parameter, only use the format yyyy-mm-dd.
Don't call this tool if the user's question cannot be answered with the provided metrics, dimensions, and entities. Instead, clarify what metrics, dimensions, and entities are available and suggest a new question that can be answered and is approximately the same as the user's question.
For queries that may return large amounts of data, it's recommended to use a two-step approach:
First make a query with a small limit to verify the results are what you expect
Then make a follow-up query without a limit (or with a larger limit) to get the full dataset
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| group_by | No | ||
| limit | No | ||
| metrics | Yes | ||
| order_by | No | ||
| where | No |
Input Schema (JSON Schema)
Implementation Reference
- MCP tool handler function for 'query_metrics'. Decorated with @dbt_mcp_tool which defines the tool schema and metadata. Dispatches to SemanticLayerFetcher.@dbt_mcp_tool( description=get_prompt("semantic_layer/query_metrics"), title="Query Metrics", read_only_hint=True, destructive_hint=False, idempotent_hint=True, ) async def query_metrics( context: SemanticLayerToolContext, metrics: list[str], group_by: list[GroupByParam] | None = None, order_by: list[OrderByParam] | None = None, where: str | None = None, limit: int | None = None, ) -> str: result = await context.semantic_layer_fetcher.query_metrics( metrics=metrics, group_by=group_by, order_by=order_by, where=where, limit=limit, ) if isinstance(result, QueryMetricsSuccess): return result.result else: return result.error
- src/dbt_mcp/mcp/server.py:135-149 (registration)Registration of semantic layer tools (including query_metrics) to the FastMCP server instance.if config.semantic_layer_config_provider: logger.info("Registering semantic layer tools") register_sl_tools( dbt_mcp, config_provider=config.semantic_layer_config_provider, client_provider=DefaultSemanticLayerClientProvider( config_provider=config.semantic_layer_config_provider, ), disabled_tools=disabled_tools, enabled_tools=enabled_tools, enabled_toolsets=enabled_toolsets, disabled_toolsets=disabled_toolsets, )
- Core implementation of query_metrics in SemanticLayerFetcher class, which performs validation, queries the dbt Semantic Layer via SDK, formats results or errors.async def query_metrics( self, metrics: list[str], group_by: list[GroupByParam] | None = None, order_by: list[OrderByParam] | None = None, where: str | None = None, limit: int | None = None, result_formatter: Callable[[pa.Table], str] | None = None, ) -> QueryMetricsResult: validation_error = await self.validate_query_metrics_params( metrics=metrics, group_by=group_by, ) if validation_error: return QueryMetricsError(error=validation_error) try: query_error = None sl_client = await self.client_provider.get_client() with sl_client.session(): # Catching any exception within the session # to ensure it is closed properly try: parsed_order_by: list[OrderBySpec] = self._get_order_bys( order_by=order_by, metrics=metrics, group_by=group_by ) query_result = await asyncio.to_thread( sl_client.query, metrics=metrics, group_by=group_by, # type: ignore order_by=parsed_order_by, # type: ignore where=[where] if where else None, limit=limit, ) except Exception as e: query_error = e if query_error: return self._format_query_failed_error(query_error) formatter = result_formatter or DEFAULT_RESULT_FORMATTER json_result = formatter(query_result) return QueryMetricsSuccess(result=json_result or "") except Exception as e: return self._format_query_failed_error(e)
- Type definitions used for query_metrics tool parameters (e.g., OrderByParam, GroupByParam from external) and responses (QueryMetricsSuccess/Error). Input schema derived from handler function signature.from dataclasses import dataclass from dbtsl.models.dimension import DimensionType from dbtsl.models.entity import EntityType from dbtsl.models.metric import MetricType @dataclass class OrderByParam: name: str descending: bool @dataclass class MetricToolResponse: name: str type: MetricType label: str | None = None description: str | None = None metadata: str | None = None @dataclass class DimensionToolResponse: name: str type: DimensionType description: str | None = None label: str | None = None granularities: list[str] | None = None @dataclass class EntityToolResponse: name: str type: EntityType description: str | None = None @dataclass class SavedQueryToolResponse: name: str label: str | None = None description: str | None = None metrics: list[str] | None = None group_by: list[str] | None = None where: list[str] | None = None @dataclass class QueryMetricsSuccess: result: str error: None = None @dataclass class QueryMetricsError: error: str result: None = None QueryMetricsResult = QueryMetricsSuccess | QueryMetricsError @dataclass class GetMetricsCompiledSqlSuccess: sql: str error: None = None @dataclass class GetMetricsCompiledSqlError: error: str sql: None = None GetMetricsCompiledSqlResult = GetMetricsCompiledSqlSuccess | GetMetricsCompiledSqlError