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    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.
    16
    39 PyPI
    2
    Apache 2.0
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    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.
    16
    MIT
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    Official MCP server for Apache Drill, enabling read-only SQL queries and inspection of schemas, storage plugins, and cluster/query state.
    9
    1
    Apache 2.0
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    An MCP server that enables users to interact with Apache Doris databases through natural language, supporting query and management operations.
    3
    Apache 2.0
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    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.
    9
    MIT
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    Backend service implementing the Model Control Panel protocol that connects to Apache Doris databases, allowing users to execute SQL queries, manage metadata, and potentially leverage LLMs for tasks like natural language to SQL conversion.
    8
    87 PyPI
    348
    Apache 2.0
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    Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9
    30
    1
    MIT
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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.
    23
    Apache 2.0
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    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.
    MIT
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    Enables interaction with Apache Airflow through the Model Context Protocol, allowing users to manage DAGs, task instances, variables, connections, pools, XComs, and datasets.
    MIT
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    Enables AI-controlled management of Apache Beam data pipelines across different runners (Flink, Spark, Dataflow, Direct) via the Model Context Protocol.
    4
    MIT
  • F
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    Enables AI assistants to query Hadoop MapReduce job history, including job listing, details, counters, configuration, and logs via the JobHistory REST API.
    1
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  • F
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    MCP server for Cloudera Manager and CDP cluster administration, enabling monitoring, configuration, and troubleshooting of Hadoop ecosystem services through natural language.
    1
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