bintocher/mcp-superset

Overview

An MCP server that exposes 128+ tools for managing Apache Superset, including dashboards, charts, datasets, SQL Lab, and access control. It operates as a Python-based server, enabling AI assistants to interact programmatically with Superset instances.

Best for

Best for
Developers and data teams who want to manage Apache Superset programmatically through AI assistants

Use cases

• Automate dashboard creation and chart configuration via natural language commands
• Manage datasets and SQL Lab queries through an AI assistant
• Programmatically control user permissions and access roles in Superset

How to use

Install

uvx mcp-superset

Tools exposed

• superset_dashboard_list
• superset_dashboard_get
• superset_dashboard_create
• superset_dashboard_update
• superset_dashboard_delete
• superset_dashboard_copy
• superset_dashboard_publish
• superset_dashboard_unpublish
• superset_dashboard_charts
• superset_dashboard_datasets
• superset_dashboard_export
• superset_dashboard_import
• superset_dashboard_embedded_get
• superset_dashboard_embedded_set
• superset_dashboard_embedded_delete
• superset_dashboard_filter_list
• superset_dashboard_filter_add
• superset_dashboard_filter_update
• superset_dashboard_filter_delete
• superset_dashboard_filter_reset

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf

Notes

An MCP server that exposes 128+ tools for managing Apache Superset, including dashboards, charts, datasets, SQL Lab, and access control. It operates as a Python-based server, enabling AI assistants to interact programmatically with Superset instances.

42 stars on GitHub. Last updated 2026-04-05. Licensed MIT.

Use cases

• Automate dashboard creation and chart configuration via natural language commands
• Manage datasets and SQL Lab queries through an AI assistant
• Programmatically control user permissions and access roles in Superset

Pros

• Extensive tool coverage with over 128 functions for comprehensive Superset management
• Open source with a permissive license and active community on GitHub
• Direct integration with MCP-compatible AI assistants for streamlined workflows

Cons

• Requires a running Superset instance and network access to function
• Limited to 42 GitHub stars, indicating a small user base and potential for fewer community resources
• Dependency on MCP protocol may restrict use to compatible AI frameworks only

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.