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Cloudera AI MCP logo

Cloudera AI MCP

adfr/MCP_cloudera

Cloudera ML Model Control Protocol (MCP) is a Python toolkit that provides integration with the Cloudera machine learning platform, including services such as file management, job scheduling, model management, and experiment tracking.

View on GitHub

Install

Client configuration

{
  "mcpServers": {
    "cloudera-ml-mcp-server": {
      "command": "python",
      "args": [
        "/path/to/MCP_cloudera/server.py"
      ],
      "env": {
        "CLOUDERA_ML_HOST": "<CLOUDERA_ML_HOST>",
        "CLOUDERA_ML_API_KEY": "<CLOUDERA_ML_API_KEY>"
      }
    }
  }
}

Environment variables

CLOUDERA_ML_HOSTCLOUDERA_ML_API_KEY
Author
@adfr
Category
Developer Tools, Cloud Platform
License
MIT
Updated
Oct 6, 2026

About Cloudera AI MCP

This MCP implements a Python-based integration with Cloudera Machine Learning, allowing Claude to interact with CML services programmatically.

Features

  • Upload Folders: Upload entire folders to your CML project while preserving directory structure

  • Create Jobs: Create new CML jobs with customizable settings

  • List Jobs: View all jobs in your project with their current status

  • Delete Jobs: Remove individual jobs or all jobs in a project

  • Get Project ID: Retrieve project ID from a project name

  • List Project Files: View files and directories in your project

  • Model Management: Create, list, and manage ML models and deployments

  • Experiment Tracking: Log and manage ML experiments and runs

  • Application Management: Create, update, and manage CML applications

Details on this page are taken from the project's README. Open README

Supported clients

Clients mentioned in this server's README:

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