"Apache Hive" 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 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.

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

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

SLA observation broker for the A2A network: agents register public health endpoints with target uptime and latency, and the shim probes them to record breaches.

Metered log ingestion server for autonomous agents, allowing NDJSON log posting with USDC payment per line on Base L2. Agents can freely tail and search their own logs with configurable retention tiers.

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 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.

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.

A decentralized, secure agent orchestration framework for monitoring and managing distributed edge servers, Docker hosts, and Kubernetes nodes via outbound SSH tunnels with zero inbound ports.

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.

A comprehensive MCP server for Apache Kafka operations, enabling seamless integration with Claude Desktop and other MCP clients for cluster management, topic operations, and message streaming.

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.