No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by aws · MCP Server · ★ 2.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-toolkit-for-aws safe to install? View the security audit →
Agent Toolkit for AWS Help AI coding agents build, deploy, and manage applications on AWS. The Agent Toolkit for AWS gives AI coding agents the tools, knowledge, and guardrails they need to work with AWS services. It works with the coding agents developers already use — including Claude Code, Codex, Cursor, and Kiro. Quick start Claude Code The plugins are available on the official Anthropic marketplace () which is added to your Claude Code installation by default. Use the following commands to install supported plugins from the toolkit: For that covers service selection, CDK/CloudFormation, serverless, containers, storage, observability, billing, SDK usage, and deployment: Tip: If you get , update your local marketplace index first: For that covers building AI agents on AWS with Amazon Bedrock and AgentCore: For that covers data l
| Stars | 2,847 |
| Forks | 361 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 68.0155065427019/100 |
| Open Issues | 67 |
| Last Updated | 2026-10-12 |
| Created | 2026-04-23 |
| Platforms | aws, mcp, python |
| Est. Tokens | ~15k |
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agent-toolkit-for-aws is Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. It is categorized as a MCP Server with 2.8k GitHub stars.
agent-toolkit-for-aws is primarily written in Python.
You can find installation instructions and usage details in the agent-toolkit-for-aws GitHub repository at github.com/aws/agent-toolkit-for-aws. The project has 2.8k stars and 361 forks, indicating an active community.
agent-toolkit-for-aws is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: