Aws Agentic Ai

Plugin Verified Active

AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, and Evaluations

1 Skill 0 MCPs

Purpose

To enable users to comprehensively deploy and manage all AWS Bedrock AgentCore services, facilitating AI agent development and operations on AWS.

Features

Expert management of AWS Bedrock AgentCore services
Support for Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, and Evaluations
Covers agent deployment, MCP tool integration, and credential management
Facilitates agent discovery, governance, and quality assessment
Utilizes AWS CLI for service interactions

Use Cases

Deploying and scaling AI agents on AWS Bedrock AgentCore
Integrating REST APIs as MCP tools using the Gateway service
Managing conversation state and credentials for AI agents
Cataloging, discovering, and governing AI agents and tools via the Agent Registry
Evaluating agent quality using LLM-as-a-Judge approaches

Non-Goals

Managing AWS services outside of Bedrock AgentCore
Providing a GUI for AWS management
Replacing the AWS console or AWS SDKs for all interactions

Installation

First, add the marketplace

/plugin marketplace add zxkane/aws-skills

/plugin install aws-agentic-ai@aws-skills

Contains 1 extensions

Skill (1)

Aws Agentic Ai Skill

AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations. Covers agent deployment, MCP tool integration, credential management, agent discovery, governance workflows, and automated quality assessment. Essential when user mentions AgentCore, agent runtime, agent registry, agent evaluation, MCP gateway, deploy agent, register MCP server, discover agents, evaluate agent quality, agent credentials, or wants to build, deploy, catalog, or monitor AI agents on AWS.

Quality Score

Verified

99 /100

Analyzed about 16 hours ago

Trust Signals

Last commit22 days ago

GitHub owner zxkane

Stars281

LicenseMIT

Websiteskills.sh

Status

View Source

Similar Extensions

Serverless Eda

AWS serverless and event-driven architecture best practices based on Well-Architected Framework with MCP servers for SAM, Lambda, Step Functions, and messaging

Plugin

zxkane

Deployment Validation

Pre-deployment checks, configuration validation, and deployment readiness assessment

Plugin

wshobson

Ruflo Agent

Agent runtimes for ruflo — local WASM-sandboxed agents (rvagent: 10 wasm_agent_*/wasm_gallery_* MCP tools, built on @ruvector/rvagent-wasm + @ruvector/ruvllm-wasm per ADR-070) plus Anthropic Claude Managed Agents as a cloud backend (managed_agent_* MCP tools per ADR-115). One interface, local-vs-cloud runtimes.

Plugin

ruvnet

Azure

Microsoft Azure MCP and Skills integration for cloud resource management, deployments, and Azure services. Manage your Azure infrastructure, monitor applications, and deploy resources directly from Claude Code.

Plugin

microsoft

Terraform Patterns

Terraform infrastructure-as-code agent skill and plugin for module design patterns, state management strategies, provider configuration, security hardening, and CI/CD plan/apply workflows. Covers mono-repo vs multi-repo, workspaces, policy-as-code, and drift detection.

Plugin

alirezarezvani

Aws Cost Ops

AWS cost optimization, monitoring, and operational excellence with integrated MCP servers for billing, cost analysis, observability, and security assessment

Plugin

zxkane