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MLflow

MLflow is an Apache 2.0 open-source platform for the end-to-end ML and GenAI lifecycle: tracking, model registry, deployment, evaluation, traces, prompts, and GenAI gateway. The tracking server exposes a REST API under `/api/2.0/mlflow`.

2 APIs 0 Features
MLMLOpsGenAIExperiment TrackingOpen Source

APIs

MLflow REST API

The MLflow tracking server exposes a REST API for experiments, runs, parameters, metrics, tags, registered models, model versions, model aliases, and artifacts, plus newer endpo...

MLflow AI Gateway API

The MLflow AI Gateway provides a unified HTTP interface to LLM providers with routing, rate-limiting, and secret management features.

Resources

🔗
Website
Website
🌐
Portal
Portal
💻
SourceCode
SourceCode
🔗
License
License
🔗
Databricks Managed MLflow
CommercialOffering
🔗
Plans
Plans
🔗
RateLimits
RateLimits
🔗
FinOps
FinOps

Sources

apis.yml Raw ↑
aid: mlflow
url: https://raw.githubusercontent.com/api-evangelist/mlflow/refs/heads/main/apis.yml
name: MLflow
x-type: opensource
description: >-
  MLflow is an Apache 2.0 open-source platform for the end-to-end ML and GenAI
  lifecycle: tracking, model registry, deployment, evaluation, traces, prompts, and
  GenAI gateway. The tracking server exposes a REST API under `/api/2.0/mlflow`.
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
  - ML
  - MLOps
  - GenAI
  - Experiment Tracking
  - Open Source
created: '2026-05-08'
modified: '2026-05-08'
specificationVersion: '0.19'
apis:
  - aid: mlflow:mlflow-tracking-rest-api
    name: MLflow REST API
    humanURL: https://mlflow.org/docs/latest/rest-api.html
    baseURL: http://{tracking_server}/api/2.0/mlflow
    tags:
      - REST
      - Experiments
      - Runs
      - Model Registry
      - Artifacts
    description: >-
      The MLflow tracking server exposes a REST API for experiments, runs, parameters,
      metrics, tags, registered models, model versions, model aliases, and artifacts,
      plus newer endpoints for traces, prompts, datasets, and the AI gateway. POST
      requests use `application/json`. Pagination via `max_results` / `page_token`.
      Authentication is deployment-specific (basic auth, OIDC, or none).
    properties:
      - type: Documentation
        url: https://mlflow.org/docs/latest/rest-api.html
      - type: SDK
        title: Python (mlflow)
        url: https://mlflow.org/docs/latest/python_api/index.html
      - type: SDK
        title: Java
        url: https://mlflow.org/docs/latest/java_api/index.html
      - type: SDK
        title: R
        url: https://mlflow.org/docs/latest/R-api.html
  - aid: mlflow:mlflow-gateway-api
    name: MLflow AI Gateway API
    humanURL: https://mlflow.org/docs/latest/llms/gateway/index.html
    baseURL: http://{gateway}/gateway
    tags:
      - GenAI
      - LLM Gateway
      - REST
    description: >-
      The MLflow AI Gateway provides a unified HTTP interface to LLM providers with
      routing, rate-limiting, and secret management features.
    properties:
      - type: Documentation
        url: https://mlflow.org/docs/latest/llms/gateway/index.html
common:
  - type: Website
    url: https://mlflow.org/
  - type: Portal
    url: https://mlflow.org/docs/latest/
  - type: SourceCode
    url: https://github.com/mlflow/mlflow
  - type: License
    url: https://github.com/mlflow/mlflow/blob/master/LICENSE.txt
  - type: CommercialOffering
    title: Databricks Managed MLflow
    url: https://www.databricks.com/product/managed-mlflow
  - type: Plans
    url: plans/mlflow-plans-pricing.yml
  - type: RateLimits
    url: rate-limits/mlflow-rate-limits.yml
  - type: FinOps
    url: finops/mlflow-finops.yml
maintainers:
  - FN: Kin Lane
    email: [email protected]