Mlflow MCP Server

Mlflow is an MCP integration. MLflow MCP — experiments, runs, registered models, versions, traces, assessments (MLflow 3).

Packages and local setup

The published npm package is @us-all/mlflow-mcp, version 1.12.7. Its declared MCP transport is stdio.

The package declares MLFLOW_TRACKING_URI (required): MLflow tracking server URI (e.g. http://localhost:5050, https://mlflow.example.com).; MLFLOW_TRACKING_TOKEN: Bearer token for authenticated MLflow servers (e.g. Databricks).; MLFLOW_TRACKING_USERNAME: Basic-auth username (alternative to token).; MLFLOW_TRACKING_PASSWORD: Basic-auth password (alternative to token).; MLFLOW_EXPERIMENT_ID: Default experiment ID for run-creation tools.; MLFLOW_TOOLS: Comma-separated category allowlist. Default: all categories enabled.; MLFLOW_DISABLE: Comma-separated category disablelist.; MLFLOW_ALLOW_WRITE: Set to 'true' to enable write/destructive tools. Default read-only..

Before connecting

Check the maintainer’s instructions for account access, authentication and the supported client configuration. Once connected, inspect the tools your client receives and try a small task that matches the server’s stated purpose. The registry description does not include a verified, complete tool list.

Project and source

View the publisher’s registry entry · Project repository. This profile uses version 1.12.7 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.

Browse related developer tools MCP servers for tools that cover the same kind of work.