The MCP-Ambari-API is a robust server designed for seamless integration with the Apache Ambari API, tailored specifically for managing Hadoop clusters. This project offers a comprehensive set of tools to facilitate various operations, from service management to configuration monitoring and request tracking, making it an essential resource for cluster administrators.

Features

• Service Management: Perform essential operations such as starting, stopping, and restarting Hadoop services.
• Cluster Monitoring: Keep tabs on the service and cluster status effectively.
• Configuration Management: Retrieve, update, and manage cluster configurations with ease.
• Request Tracking: Monitor the status and progress of ongoing requests to ensure smooth operations.

Available MCP Tools

The MCP server encompasses a variety of powerful tools designed for efficient Ambari cluster management:

Cluster Management

• get_cluster_info: Retrieve basic information and status of the cluster.
• get_active_requests: List all currently active or running operations.
• get_request_status: Check the status and progress of specific requests.

Service Management

• get_cluster_services: Acquire a list of all cluster services along with their status.
• get_service_status: Obtain detailed status information for a specific service.
• get_service_components: List components and their host assignments for a designated service.
• get_service_details: Access comprehensive information regarding a specific service.
• start_service, stop_service, restart_service: Control specific services within the cluster.
• start_all_services, stop_all_services, restart_all_services: Manage all services in the cluster collectively.

Configuration Management

• get_configurations: Retrieve service configuration types and their corresponding values.
• list_configurations: List all available configuration types present in the cluster.

Host Management

• list_hosts: Generate a list of all hosts associated with the cluster.
• get_host_details: Access detailed information for specific or all hosts.

Main Tool Files

• Primary MCP tool file: src/mcp_ambari_api/ambari_api.py
• Utility functions: src/mcp_ambari_api/functions.py

For cluster management operation and tool utilization, integrating the MCP API with the existing tools framework is straightforward. It requires simple configurations in the mcp-config.json, ensuring effective connectivity to the Ambari cluster.

Example Configuration:

{
  "mcpServers": {
    "ambar-api": {
      "command": "uvx",
      "args": ["--python", "3.11", "mcp-ambari-api"],
      "env": {
        "AMBARI_HOST": "host.docker.internal",
        "AMBARI_PORT": "8080",
        "AMBARI_USER": "admin",
        "AMBARI_PASS": "admin",
        "AMBARI_CLUSTER_NAME": "TEST-AMBARI"
      }
    }
  }
}

Self QuickStart: Setting Up MCP Tools Environment with Docker

This section outlines the steps to set up the MCP Tools environment to manage an Ambari cluster effectively. The recommended setup utilizes Docker for easy deployment and contains vital guidelines for integrating the MCPO Proxy and OpenWebUI environments.

Environment Requirements:

• Tested on WSL2 Linux with Windows 11
• Ambari 3.0 cluster setup is required.

Setting Up the Environment:

1. Prepare your Ambari cluster by following the guide Install Ambari 3.0 with Docker.
2. Verify environment variables in your mcp-config.json file to ensure compatibility with your Amber cluster settings.
3. Start the environment using Docker Compose:

docker-compose up -d

The OpenWebUI interface can be accessed via the specified port (e.g., [http://localhost:3000](http://localhost:3000)). For API requests, use the MCPO-Proxy, listening on another defined port.

### Example Usage:
The MCP Tools provide various functionalities, like querying cluster information and reviewing configurations through intuitive commands and UI interactions. Users can easily visualize and manage tasks such as restarting services or checking the overall health of the cluster.

## Roadmap
The MCP-Ambari-API project is continuously evolving, with plans to enhance its capabilities further. The roadmap includes the addition of user and permission management, advanced configurations, and enhanced tracking features based on community feedback and practical needs.