The Open Source AI Engineering Platform for Agents, LLMs & Models

MLflow is the largest open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data. With over 60 million monthly downloads, thousands of organizations rely on MLflow each day to ship AI to production with confidence.

MLflow's comprehensive feature set for agents and LLM applications includes production-grade observability, evaluation, prompt management, prompt optimization and an AI Gateway for managing costs and model access. Learn more at MLflow for LLMs and Agents.

Get Started in 3 Simple Steps

From zero to full-stack LLMOps in minutes. No complex setup or major code changes required. Get Started →

Fastest start — set up tracing with our CLI

uvx mlflow@latest agent setup

One command installs the MLflow skills and launches your coding agent of choice to add tracing to your app. Prefer to wire it up yourself? Follow the three steps below.

1. Start MLflow Server

uvx mlflow server

2. Enable Logging

import mlflow

mlflow.set_tracking_uri("http://localhost:5000")
mlflow.openai.autolog()

3. Run Your Code

from openai import OpenAI

client = OpenAI()
client.responses.create(
    model="gpt-5.4-mini",
    input="Hello!",
)

Explore traces and metrics in the MLflow UI at http://localhost:5000.

LLMs & Agents

MLflow provides everything you need to build, debug, evaluate, and deploy production-quality LLM applications and AI agents. Supports Python, TypeScript/JavaScript, Java and any other programming language. MLflow also natively integrates with OpenTelemetry and MCP.

Observability Capture complete traces of your LLM applications and agents for deep behavioral insights. Built on OpenTelemetry, supporting any LLM pr