MCP-Ambari-API

MCP-Ambari-API is an MCP server that connects LLM clients directly to Apache Ambari and Ambari Metrics Service for automated cluster operations. Designed for DevOps engineers, data engineers, and infrastructure administrators, this server provides a natural language interface to manage Hadoop clusters without manual console or UI intervention. It exposes tools to check cluster health, inspect configurations, stop and restart Hadoop services, track asynchronous Ambari requests, and monitor host statuses across nodes. Through its deterministic Ambari Metrics integration, users can discover exact application IDs like NameNode or DataNode, search metadata catalogs, and retrieve time-series performance data such as memory heap consumption or disk usage. The server also generates operational summaries mirroring standard HDFS administration commands. By supporting both stdio and streamable HTTP transports alongside containerized deployment models, MCP-Ambari-API integrates with frontends like OpenWebUI to streamline cluster troubleshooting, maintenance workflows, and capacity tracking.

Category: Cloud & Infrastructure

Tags: apache-ambari, big-data, cluster-management, hadoop

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How to install and configure MCP-Ambari-API

1. Clone the repository: git clone https://github.com/call518/MCP-Ambari-API and navigate to the project directory. 2. Copy the environment configuration template: cp .env.example .env. 3. Open .env and set your connection parameters, including AMBARI_HOST, AMBARI_PORT, AMBARI_USER, AMBARI_PASS, AMBARI_CLUSTER_NAME, and AMS metrics settings. 4. Start the stack using Docker Compose: docker-compose up -d. 5. To register the tool with a client such as OpenWebUI, log in as an administrator, navigate to Settings > Tools, and add the server tool address (for example, http://localhost:8000/mcp-ambari-api).

What you can do with MCP-Ambari-API

• Query real-time status, alerts, and operational health summaries for all components across an Apache Ambari cluster. - Restart or manage Hadoop services like HDFS, YARN, and NameNode directly using automated natural language requests. - Fetch exact time-series performance metrics for hosts and services from Ambari Metrics Service without writing manual API queries. - Generate DFSAdmin-style HDFS capacity reports and node summary overviews directly inside AI chat sessions.

Key facts

• https://github.com/call518/MCP-Ambari-API
• Cloud & Infrastructure, Monitoring & Observability
• apache-ambari, big-data, cluster-management, hadoop

Part of MCP Servers

What is MCP-Ambari-API?

MCP-Ambari-API is an open source Model Context Protocol server that bridges AI models and clients with Apache Ambari REST APIs. It allows administrators to run cluster queries, execute service control actions, and view time-series monitoring metrics using natural language.

How do I install MCP-Ambari-API?

You install it by cloning the GitHub repository, configuring an environment file with your Ambari server host, credentials, and cluster details, and starting the containers using Docker Compose. It can then be registered in compatible MCP clients via its HTTP or stdio endpoint.

What license does MCP-Ambari-API use?

MCP-Ambari-API is released under the open source MIT License, as indicated in its GitHub repository documentation and project badges.

What can MCP-Ambari-API do?

The server can inspect cluster configurations, run HDFS capacity reports, restart services, track active Ambari tasks, discover Ambari Metrics Service application IDs, and execute precise time-series queries for components like DataNodes and NameNodes.

Which MCP clients work with MCP-Ambari-API?

It works with MCP-compatible clients that support Model Context Protocol tool registration, including OpenWebUI, MCPO OpenAPI proxies, and other standard MCP clients communicating over stdio or streamable HTTP.