An MCP server that gives AI agents the ability to profile a CSV, define an ML task, tune XGBoost and LightGBM with Optuna, and produce a markdown report with feature importance, all from natural language.
Enables training and using machine learning models on local CSV datasets or data from other MCP servers, supporting tasks like forecasting, regression, classification, and anomaly detection.
MCP server that wraps the Picsellia Python SDK, giving AI assistants access to computer vision platform capabilities such as datasets, experiments, models, deployments, and monitoring.
A standalone MCP server that brings complete data science capabilities to AI assistants, enabling them to load data, train models, and track experiments through natural language.
An MCP server that enables automated dataset creation and custom object detection model training through natural language interactions. It integrates foundation models like GroundedSAM for auto-labeling and supports training specialized YOLOv8 models using local or Unsplash images.
