MLflow Agent

MLflow MCP Server provides a natural language interface to MLflow tracking servers through the Model Context Protocol, enabling AI assistants to query and manage machine learning experiments and models using plain English. Developed by Rahul Pandey, this implementation connects to a local MLflow server and exposes core functionality through four standardized tools: listing registered models, listing experiments, retrieving detailed model information, and getting system status. The server is designed for data scientists and ML engineers who want to simplify their MLflow workflows by interacting with their experiment tracking and model registry through conversational AI.