"Running queries in Apache Superset" matching MCP servers:

Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.

An MCP server that wraps the Apache Airflow REST API, enabling clients to manage DAGs, monitor task instances, and handle workflows through a standardized interface. It provides comprehensive access to Airflow features including DAG runs, variables, connections, and XComs.

MCP server that lets AI assistants and LLMs interact with Apache Flink clusters through natural language: cluster/job monitoring, metrics, exception tracking, TaskManager resources, and multi-cluster support via the Flink REST API.

Exposes Spark History Server data as tools for AI agents, enabling natural language querying of Spark applications, jobs, stages, and performance metrics.

An MCP server for querying and analyzing Apache Incubator podling health reports. It provides tools to list, search, and compare podling metrics across different time windows from Apache's health report Markdown files.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

DBeast MCP is a robust, security-first Model Context Protocol server designed to empower AI coding assistants (like Claude Desktop) with deep PostgreSQL database insights. Instead of just running basic SQL queries, DBeast equips your AI agent with tools to inspect active locks, audit slow queries, analyze table schemas, and safely generate index recommendations in real-time. Built specifically for

Enables running, monitoring, and managing ANUGA flood simulations on Hydrata Cloud, supporting project listing, scenario queries, simulation start, status polling, cancellation, and retry operations.

Enables MCP clients and AI agents to inspect a running FLECS application through its built-in REST API, including querying entities, reading components, explaining queries, and inspecting systems and performance statistics. With explicit opt-in, it also allows small reversible changes to the live ECS world.

A read-only MCP server for Microsoft SQL Server that allows running SELECT queries and analyzing query performance with statistics.

Enables AI agents to diagnose broken XAMPP/WAMP localhost stacks by inspecting real machine state — running processes, listening ports, HTTP probes, and Apache/MySQL error logs — to pinpoint port conflicts, startup crashes, unclean-shutdown damage, and zombie processes with plain-English explanations. All diagnostics are read-only, so agents can safely answer questions like why Apache won't start or why localhost refuses to connect instead of guessing.

Enables AI agents to investigate Splunk exports or live queries using deterministic detectors and an iterative analysis loop, all running locally without data leaving the machine.

MCP server for Apache Kafka that allows LLM agents to inspect topics, consumer groups, and safely manage offsets (reset, rewind).

Enables read-only access to Google Analytics 4 properties through MCP tools for listing properties, inspecting metadata, checking metric compatibility, and running core or realtime reports, summaries, traffic-source, page, and event queries.

Enables AI assistants to manage Apache Ambari clusters, including services, hosts, alerts, and configurations via the MCP protocol.

MCP server that lets LLMs interact with a running Prometheus instance via its API, enabling metric analysis, PromQL queries, and rule/target inspection. It also provides embedded documentation and guided runbooks for common Prometheus tasks.

Enables AI assistants to perform automated root-cause analysis of slow Apache Spark and Databricks jobs by listing applications, planning and running diagnoses, retrieving stage and SQL plan details, and listing diagnosis rules via read-only MCP tools.

Enables AI assistants to programmatically create, execute, and analyze Apache JMeter performance tests. It supports automated bottleneck detection, report generation, and distributed testing management through natural language.

Read-only MCP server exposing Flowsery analytics and AI-detected issues via 17 GET tools, enabling natural language queries in compatible clients.

Enables AI assistants to understand Apache NiFi flows, investigate failures with cited evidence, and draft reviewable flow files while keeping live NiFi access read-only.

Enables AI-assisted management of Apache Tomcat, including start/stop, WAR deployment, log analysis, thread and heap dumps, and diagnostics.

An MCP server that gives AI agents real-time observability into Apache Kafka clusters, enabling natural language queries for broker health, consumer lag, and diagnostics.

Provides read-only monitoring of Apache Airflow DAGs, including listing active DAGs, fetching recent runs, and analyzing execution history and performance metrics.

MCP server for InfluxDB 2.x, tuned for Home Assistant long-term storage, enabling reading sensor history, finding anomalies, and running Flux queries.

Enables monitoring and management of Apache Cassandra and DataStax Enterprise clusters through the DataStax OpsCenter API, providing tools for cluster metrics, node monitoring, schema access, and event tracking.

Enables users to interact with Apache Airflow orchestration platform through natural language to query pipeline statuses, troubleshoot DAG failures, trigger DAGs, and analyze configurations.

Enables DAG management, monitoring, debugging, and connection testing for Apache Airflow through the MCP protocol.

Enables AI assistants to manage and monitor Apache Kafka clusters through natural language, providing real-time operations, health monitoring, consumer lag analysis, and temporal trend detection for intelligent cluster management.

Deploys 25 MCP tools for Apache Doris, enabling SQL execution, metadata queries, monitoring, and data governance over HTTPS via AWS Bedrock AgentCore Runtime.