Enables AI assistants to interact with MLflow experiments, runs, and registered models. Supports browsing experiments, retrieving run details with metrics and parameters, and querying the model registry through natural language.
A natural language interface for MLflow that allows users to query and manage their machine learning experiments and models using plain English through the Model Context Protocol.
Enables AI agents to plan, submit, monitor, and manage Kubeflow training jobs through natural language, without needing to learn Kubernetes or the Kubeflow SDK.
Enables interaction with Cloudera Machine Learning to manage projects, files, and jobs through the Model Context Protocol. It supports tasks such as uploading files, scheduling jobs, and managing runtimes via natural language interfaces.
Enables AI assistants to perform MLOps workflows such as experiment tracking, model registry, dataset management, pipeline orchestration, and data lineage by wrapping DVC, MLflow, and Git.
Provides a chat interface with natural language processing to deploy and manage AWS resources through an integrated Model Context Protocol (MCP) server.
