Amazon SageMaker · Capability
Amazon SageMaker ML Lifecycle Management
Unified capability for managing the end-to-end machine learning lifecycle including notebook development, training, model management, and endpoint deployment. Used by ML Engineers and Data Scientists.
What You Can Do
GET
List notebooks
— List all SageMaker notebook instances
/v1/notebooks
POST
Create notebook
— Create a SageMaker notebook instance for ML development
/v1/notebooks
GET
List training jobs
— List all SageMaker training jobs
/v1/training-jobs
POST
Create training job
— Submit a new model training job
/v1/training-jobs
GET
List models
— List all registered SageMaker models
/v1/models
POST
Register model
— Register a trained model for deployment
/v1/models
GET
List endpoints
— List all SageMaker inference endpoints
/v1/endpoints
POST
Deploy endpoint
— Deploy a model to a SageMaker inference endpoint
/v1/endpoints
MCP Tools
list-notebook-instances
List SageMaker Jupyter notebook instances for ML development
read-only
idempotent
create-notebook-instance
Create a SageMaker Jupyter notebook instance
list-training-jobs
List SageMaker model training jobs
read-only
idempotent
create-training-job
Submit a SageMaker model training job
describe-training-job
Get details about a specific SageMaker training job
read-only
idempotent
list-models
List registered SageMaker ML models
read-only
idempotent
create-model
Register a trained model in SageMaker
list-endpoints
List active SageMaker inference endpoints
read-only
idempotent
deploy-endpoint
Deploy a model to a SageMaker inference endpoint
describe-endpoint
Get the status and details of a SageMaker inference endpoint
read-only
idempotent
APIs Used
amazon-sagemaker