aws-mcp-server: A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context

by alexei-led · MCP Server · ★ 180

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-assistantawsaws-automationclaudecloud-infrastructuredevopsdockermcpmcp-servermodelcontextprotocol

Quick Facts

Stars180
Forks31
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score75/100
Last Updated2026-02-27
Created2025-03-19
Platformsaws, claude-code, cli, docker, mcp, python
Est. Tokens~383k

About aws-mcp-server

AWS MCP Server Give Claude access to all 200+ AWS services through the AWS CLI. Demo...

Compatible Skills

These tools work well together with aws-mcp-server for enhanced workflows:

  • aws-agent-skills — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)
  • developer-kit — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • Agentic-AI-Pipeline — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • kiro-gateway — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)
  • aws-skills — semantic(0.42)+complementary+rare_topics+similar_pop+shared_platform (54%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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