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Manage Apache Superset datasets, metrics, and SQL queries with natural language.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "superset-mcp" yet — see the docs or source repo.
In Apache Superset, create a dataset for the sales.orders table and add two metrics: total sales (sum of amount) and order count (count of order_id). Then return a summary of the configuration.
A summary of the created dataset and metrics, including names, fields, and configuration status.
Review this Superset SQL query for monthly revenue analysis, identify potential issues, and provide an optimized version: SELECT date, revenue FROM finance_report.
An explanation of issues, optimization suggestions, and an improved SQL query ready to use.
List all metrics in the current Superset project, group them by dataset, flag poorly named or duplicate metrics, and provide cleanup recommendations.
A dataset-grouped metric inventory with naming standardization and deduplication recommendations.
Query and manage Superset dashboard metadata, activity, lineage, and changes.
Connect AI to Apache Superset for dashboards, datasets, and SQL analysis.
Connect to dbt via MCP to inspect projects and run data workflows.
Generate MCP tools from API specs and query them in natural language.
Enable AI to safely analyze business metrics without improvising raw SQL.
Query metrics and dimensions with MetricFlow through natural language interfaces.