Cloudera AI MCP
What is Cloudera AI MCP?
Cloudera AI MCP (Model Control Protocol) is a Python-based integration tool that allows users to interact programmatically with Cloudera Machine Learning (CML) services for managing jobs, applications, and machine learning models.
How to use Cloudera AI MCP?
To use Cloudera AI MCP, clone the repository, install the required dependencies, configure your CML instance URL and API key, and run the server. You can also use it directly in your Python code or via command-line testing.
Key features of Cloudera AI MCP?
- Upload entire folders to CML projects while preserving directory structure.
- Create, list, and delete jobs in your CML project.
- Manage ML models and deployments.
- Track and log ML experiments and runs.
- Create and manage CML applications.
Use cases of Cloudera AI MCP?
- Automating the management of machine learning jobs in CML.
- Facilitating the deployment of ML models in production environments.
- Streamlining the process of tracking experiments and results in machine learning projects.
FAQ from Cloudera AI MCP?
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What programming language is Cloudera AI MCP written in?
Cloudera AI MCP is written in Python.
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Is there a graphical user interface for Cloudera AI MCP?
No, Cloudera AI MCP is designed for programmatic access and does not include a GUI.
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What are the system requirements?
Cloudera AI MCP requires Python 3.8 or higher and several Python packages as specified in the requirements.