Superset MCP
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Alternatives to Superset MCP
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Related Servers
- AlicenseNot gradedqualityCmaintenanceA comprehensive MCP server for Apache Superset. Gives AI assistants full control over your Superset instance — dashboards, charts, datasets, SQL Lab, users, roles, RLS, and more — through 137 tools.MIT
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- AlicenseBqualityCmaintenanceMCP server for Preset (managed Apache Superset). Manage dashboards, charts, and datasets from Claude Code and other LLM agents.591MIT
- AlicenseBqualityFmaintenanceMCP server enabling AI agents to programmatically connect to and control Apache Superset instances, allowing users to manage dashboards, charts, databases, datasets, and run SQL queries through natural language interactions.60195MIT
- FlicenseNot gradedqualityBmaintenanceEnables AI agents to manage Apache Superset BI metadata (charts, dashboards, datasets, and queries) via MCP, with a read-only default and optional governed write access.-
- AlicenseAqualityAmaintenanceFull-featured MCP server for Apache Superset — 135+ tools for dashboards, charts, datasets, SQL Lab, security (users, roles, RLS, groups), audit, and more. Built-in safety validations.1001,181 PyPI60MIT
TDQS
Scored across 60 tools
Most tools pair a distinct resource with a distinct action (e.g., chart_create vs chart_delete vs dashboard_create), so misselection is limited. However, SQL-related tools such as query_list, sqllab_get_saved_queries, and saved_query_get_by_id overlap conceptually, and the many database inspection helpers are closely related.
Almost all tools follow a clear superset_<domain>_<action> snake_case convention, with predictable verbs like create, update, delete, list, and get_by_id. Minor deviations exist, such as superset_tag_objects lacking a verb and saved-query tools being split between sqllab_ and saved_query_ prefixes.
With 60 tools, the surface is far beyond the typical 3-15 range and fragments the Superset API into very narrow endpoint wrappers. Many database and SQL Lab operations could be consolidated, making the set feel excessively heavy for an MCP server.
The server covers core CRUD lifecycles for charts, dashboards, databases, and tags, and includes SQL Lab, auth, user, and explore functionality. Some gaps remain, such as dataset update/delete, saved query update/delete, and tag update, but major workflows are available.