Bring Data Visualization
to Claude Code

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.