Installing Amazon SageMaker AI skills - Amazon SageMaker AI
Agent SkillsMCP ServersInstall Skills with npx skills
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Installing Amazon SageMaker AI skills

This Amazon SageMaker AI plugin is available on the AWSLabs GitHub page and brings deep AWS AI/ML expertise directly into your coding assistant, covering the surface area of Amazon SageMaker AI; currently, skills are provided to assist with the following capability areas:

  • Model Customization — End-to-end guided workflows for fine-tuning foundation models, from use case definition through data preparation, training, evaluation, and deployment on Amazon SageMaker AI.

  • HyperPod Cluster Operations — Remote command execution on nodes via SSM, version checking, and diagnostic reporting for Amazon SageMaker AI HyperPod training clusters.

Agent Skills

The following skills are installed by the plugin:

Amazon SageMaker AI agent skills
Skill Description Documentation
planning Builds a dynamic, step-by-step plan tailored to your intents SKILL.md
directory-management Manages project directory setup, artifact organization, and plan association for new or existing projects SKILL.md
use-case-specification Guided, conversational process to define your model customization use case goals, key stakeholders, and success criteria SKILL.md
dataset-evaluation Dataset quality validation, format detection, and data requirements analysis SKILL.md
dataset-transformation Dataset format conversion and preparation for SageMaker AI-compatible training formats SKILL.md
finetuning-setup Fine-tuning technique selection (SFT, DPO, RLVR, etc.) and base model selection SKILL.md
finetuning Hyperparameter configuration and training job execution SKILL.md
model-evaluation Evaluation design, benchmark selection, LLM-as-a-judge, and model comparison SKILL.md
model-deployment Deployment configuration and endpoint setup (SageMaker AI or Amazon Bedrock) SKILL.md
hyperpod-ssm Remote command execution and file transfer on HyperPod cluster nodes via SSM SKILL.md
hyperpod-version-checker Check and compare software component versions across HyperPod cluster nodes SKILL.md
hyperpod-issue-report Generate diagnostic reports for HyperPod troubleshooting and support cases SKILL.md

MCP Servers

Amazon SageMaker AI Skills requires the Amazon SageMaker AI MCP server. Add the contents of the .mcp.json file to your platform's MCP configuration file:

  • Claude Code: Run claude mcp add --transport stdio aws-mcp -- uvx mcp-proxy-for-aws@latest https://aws-mcp.us-east-1.api.aws/mcp or manually add to User/Project/Local location as needed (Claude Code Docs: What uses scopes).

  • Cursor: .cursor/mcp.json

  • Kiro: .kiro/settings/mcp.json

Install Skills with npx skills

You may use the Skills CLI (from Vercel Labs) to install the skills into your platform:

  • Claude Code:

    npx skills add https://github.com/awslabs/agent-plugins/tree/main/plugins/sagemaker-ai/skills --all --agent claude-code --copy

  • Cursor:

    npx skills add https://github.com/awslabs/agent-plugins/tree/main/plugins/sagemaker-ai/skills --all --agent cursor --copy

  • Kiro:

    npx skills add https://github.com/awslabs/agent-plugins/tree/main/plugins/sagemaker-ai/skills --all --agent kiro-cli --copy

If you have configured other agents, use:

npx skills add https://github.com/awslabs/agent-plugins/tree/main/plugins/sagemaker-ai/skills --all --agent