"Apache Pulsar" matching MCP servers:

Integration with Timeplus, a database for streaming data, such as Apache Kafka/Pulsar

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.

Connects LLM agents to Apache Atlas for searching, tracing lineage, and managing metadata. Read-only by default, with optional write mode for creating entities and classifications.

Enables lookups across Apache Iceberg Javadocs, local source evidence, and Iceberg REST Catalog operations through MCP tools and prompts.

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

Official MCP server for Apache Drill, enabling read-only SQL queries and inspection of schemas, storage plugins, and cluster/query state.

An MCP server that enables users to interact with Apache Doris databases through natural language, supporting query and management operations.

A Model Context Protocol server that provides seamless access to multiple storage services including S3, Azure Blob Storage, and Google Cloud Storage through Apache OpenDAL™.

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

MCP server that integrates Apache Ranger authorization with RAG, enforcing Ranger policies to control access to knowledge bases before forwarding queries to RAG Studio.

The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.

Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share, governance. Anchored on COTI V2 mainnet. Apache-2.0.

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.

Provides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.

MCP server for answering questions about Apache Software Foundation policies, offering tools to list, retrieve, and search policy documents on releases, licensing, branding, security, infrastructure, and incubator topics.

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

A Model Context Protocol (MCP) server that interfaces with the Apache YuniKorn Scheduler, allowing AI agents to observe and reason about Kubernetes batch workload resource management, queue hierarchies, and application states.

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

An AI-native control interface for OCI Streaming with Apache Kafka that enables LLM agents to securely manage Kafka clusters through structured tool execution with safety guardrails.

Enables AI assistants to answer questions about Apache Iggy using the project's current guides and Rust API documentation, with search, retrieval, and documentation analysis tools.