Apache Superset MCP Server

Empower your conversational AI with deep Business Intelligence access by integrating the Apache Superset MCP connector. Seamlessly navigating complex data ecosystems natively from your LLM text-interface, your agent can comprehensively index your analytical infrastructure—spanning from high-level operational dashboards down to specific raw database connections. Instantly run ad-hoc data investigations utilizing internal SQL Lab queries, retrieve explicit graph metadata, and dynamically aggregate critical business insights without abandoning your development environment.

What you can do

• Discover Analytics Surfaces — Audit your entire BI portal intuitively by executing list_dashboards and retrieve exact metric configurations invoking get_dashboard_details.
• Graph & Dataset Inspection — Inventory active metrics logic seamlessly via list_charts (or specify via get_chart_details) and map semantic layers dynamically performing list_datasets.
• Uncover Data Architectures — Examine exact backend storage clusters accurately parsing data availability via list_databases natively.
• Direct SQL Processing — Interface with your central storage matrices seamlessly by generating raw extractions securely via execute_sql_query targeting specific analytic connections.

How it works

1. Append the Apache Superset MCP module systematically into your operational integrations panel.
2. Configure your agent accurately providing your active SUPERSET_BASE_URL alongside your validated SUPERSET_ACCESS_TOKEN acquired from Superset's security endpoint.
3. Demand direct analytic insights immediately: "Analyze our main Sales dashboard, retrieve the performance dataset logic, and execute a SQL query filtering for Q3 results directly on its database."

Who is this for?

• Data Analysts & Scientists — Expedite query composition flawlessly extracting dataset contexts and formulating complex SQL checks natively utilizing your AI assistant.
• Product Management teams — Check dashboard parameters and inspect metric shifts seamlessly via conversational interfaces over Slack or CLI without learning BI navigation.
• Data Engineering Leads — Audit operational reports safely probing exact table usage or testing semantic datasets cleanly isolating anomalies iteratively.