"Apache JMeter" matching MCP servers:

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

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

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

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.

A tool that converts natural-language requests into full, deployable, execution-verified Apache Flink SQL jobs by orchestrating an LLM to draft specs, generate Flink SQL, and verify correctness against real Flink clusters and streaming semantics—including windowed aggregates, joins, Kafka grounding, and Deployable pipelines via the generate_flink_job, ground_kafka_topic, and deploy_to_kafka tools.

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

MCP server for chatting with physical-world data from robotics, drones, automotive, and IoT sources using natural language. It generates auditable SQL queries over Apache Arrow/DuckDB to let you analyze, summarize, and build data pipelines.

Enables AI agents to safely query and explore Apache Impala clusters with read-only SQL, metadata, statistics, cluster overview, and analysis prompt templates.

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.

Enables AI agents to list metrics and dimensions, inspect definitions, and run governed metric queries against Apache Iceberg tables through a semantic layer, without writing SQL or accessing raw rows or columns outside their role.

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

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

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.

MCP server that provides AI assistants direct access to the Apache Zeppelin REST API for data engineering workflows, enabling notebook and paragraph management, execution, and interpreter control.

Enables converting data structure definitions between numerous schema formats and generating code for multiple programming languages, using Apache Avro Schema as the integration model.

Provides AI-assisted guidance for the Weik.io integration platform, enabling planning, implementation, testing, and deployment of integrations using Apache Camel and specialized Weik.io features.

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 interaction with Apache Pulsar clusters through MCP-compatible clients, supporting publish, consume, topic management, and connector operations.

Enables large language models and AI agents to securely and efficiently interact with Apache Kafka clusters through the Model Context Protocol.

Generates Apache ECharts diagrams and charts with AI dynamically, supporting all ECharts features and exporting to png, svg, and option formats.

Production-ready MCP server for Apache DolphinScheduler. Enables AI agents to operate data workflows end-to-end with 58 tools covering DAG creation, schedule management, instance control, guided troubleshooting, serial backfills, and version rollback.

A Model Context Protocol server that exposes Apache Airflow's REST API to AI agents, enabling them to inspect and operate on DAGs, DAG runs, task instances, and logs.

Enables read-only access to Apache Iceberg tables via Impala, allowing LLMs to inspect database schemas and execute SQL queries to retrieve data from Iceberg tables.

Enables MCP clients to discover processor and controller service types, build and wire Apache NiFi 2.x process groups, schedule them, and debug queues and bulletins through the NiFi REST API. Supports flow spec application, automatic canvas layout, parameter contexts, and an optional read-only mode that blocks all writes.

Enables AI agents to manage and interact with Apache NiFi through its REST API, covering process groups, processors, connections, queues, provenance, and version control via natural language tool calls.

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.

Enables read-only monitoring and diagnostics of Apache Flink clusters through a JobManager REST endpoint, including job, checkpoint, backpressure, TaskManager, and multi-cluster overviews with LLM-friendly summaries.

Enables AI assistants to interact with Apache Kafka clusters through AKHQ's REST API. Supports multi-environment configuration, flexible authentication, and comprehensive coverage of topics, consumer groups, schema registry, Kafka Connect, ksqlDB, and ACLs.

Enables users to interact with Apache Airflow through MCP to monitor DAGs, inspect runs and logs, and diagnose task failures using natural language.