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 Model Context Protocol server that enables LLMs to interact with MLflow tracking servers, allowing users to query experiments, analyze runs, compare metrics, manage the model registry, and promote models 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 access to prompt templates managed in MLflow through Claude Desktop, allowing users to instruct Claude with saved templates for repetitive tasks or common workflows.
Enables creation, management, and deployment of n8n workflows with enhanced context and automation capabilities. Features code extraction, automatic documentation, template generation, and intelligent project organization for streamlined workflow development.
Enables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.
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.