Preset MCP Datasets

preset-mcp-datasets

Use for dataset-centered MCP workflows.

Always

• Use list_datasets and get_dataset_info for dataset discovery.
• Respect permission-denied responses; do not work around them with chart, dashboard, SQL, or API calls.
• Use saved metrics and dimensions from get_dataset_info; query_dataset accepts saved metrics only, not ad-hoc expressions. When no saved metric fits, compute the aggregate with execute_sql (route to preset-mcp-sqllab) instead of guessing metric names or stopping to ask.
• Use query_dataset for semantic-layer data results.
• Use create_virtual_dataset only when the user wants to save SQL as a chartable dataset.

Decision Rules

• Metadata only: list_datasets, get_dataset_info.
• Result table from metrics/dimensions: route through preset-mcp-data / query_dataset.
• SQL-to-chartable-dataset workflow: create_virtual_dataset.
• Visualization from dataset: route to preset-mcp-visualization.
• Database discovery: use list_databases and get_database_info through discovery.

Workflow Order

1. Find the dataset with one list/search call (use a search filter and sufficient page_size); paginate or refine the filter only when the target is not in the returned page.
2. Inspect columns and metrics with one get_dataset_info call before data or chart workflows.
3. Query semantic-layer results only when the user asks for data.
4. Save virtual datasets only when persistence is requested.

Retrieve

• Dataset workflows: references/dataset-workflows.md