"Running queries in Apache Superset" matching MCP servers:

A Model Context Protocol (MCP) server for managing Apache Superset datasets, metrics, and SQL queries.

Full-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.

An MCP server that provides AI assistants with full access to Apache Superset instances, enabling interaction with dashboards, charts, datasets, databases, and SQL execution capabilities.

An MCP server for Apache Superset that enables AI models to manage dashboards, create charts with auto-detection, and execute SQL queries programmatically. It utilizes stateless HTTP transport to ensure compatibility with integration tools like Open WebUI.

Enables MCP-capable agents to inspect, validate, search, and manage Apache Hop pipelines and workflows, with guarded editing, backup, and optional local or Hop Server execution.

Enables LLM agents to interact with Apache Zeppelin notebooks via the Zeppelin REST API, supporting operations like listing, searching, editing, and running notebooks.

Enables interaction with Apache Airflow through the Model Context Protocol, allowing users to manage DAGs, task instances, variables, connections, pools, XComs, and datasets.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

Enables LLM agents to query Apache Hive/HiveServer2 by listing tables and running read-only SQL, with results returned as JSON.

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A FastMCP integration server that provides access to Apache Gravitino metadata management APIs, allowing users to manage catalog/schema/table metadata, tags, and user-role information through a structured interface.

Enables AI-controlled management of Apache Beam data pipelines across different runners (Flink, Spark, Dataflow, Direct) via the Model Context Protocol.

MCP server for configuring the konsol Frappe app via the CLI. Enables AI clients to manage dimensions, measures, fact tables, connectors, and schemas using natural language.

Enables AI assistants to audit data governance, check access control roles, query namespaces, and inspect Iceberg metadata.

An MCP server that converts Apache Airflow DAGs into Prefect flows. It provides tools to read DAGs, lookup translation knowledge, validate code, search Prefect docs, scaffold projects, deploy, and generate migration reports.

MCP server exposing Apache Airflow REST API operations as tools — list DAGs, inspect runs and task instances, trigger DAG runs, and check failed DAGs and scheduler health

Enables MCP-capable clients to monitor and manage Apache Kafka clusters, including topics, partitions, configs, and consumer groups with lag, while enforcing configurable security modes, topic allowlists, protected topics, and audit logging.

Enables Claude to inspect and operate Apache Airflow over its REST API, providing read tools and safe write operations (gated by read-only mode) for managing DAGs, runs, tasks, and pools.

Provides read-only SQL access to Apache Iceberg tables via HiveServer2, enabling querying, schema discovery, and database listing on Cloudera Data Platform.

Enables AI assistants to securely connect to Snowflake data warehouses and execute SQL queries through natural language interactions. Supports multiple authentication methods and provides formatted query results with built-in security controls.