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Aws Mcp Setup

Community
zxkane
aws-mcp-setup

Configure AWS MCP servers for documentation search and API access. Use when setting up AWS MCP, configuring AWS documentation tools, troubleshooting MCP connectivity, or when user mentions aws-mcp, awsdocs, uvx setup, or MCP server configuration. Covers both Full AWS MCP Server (with uvx + credentials) and lightweight Documentation MCP (no auth required).

Overview

Publisherzxkane
Repositoryaws-skills
Skill nameaws-mcp-setup
Stars
370
Forks
39
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by zxkane on GitHub. Read the source before you install it.

Installation

Install the Aws Mcp Setup AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zxkane/aws-skills/tree/main/plugins/aws-common/skills/aws-mcp-setup
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zxkane/aws-skills.git /tmp/aws-skills
mkdir -p .claude/skills
cp -r /tmp/aws-skills/plugins/aws-common/skills/aws-mcp-setup .claude/skills/aws-mcp-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Mcp Setup in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Mcp Setup on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Mcp Setup is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS MCP Server Configuration Guide

Overview

This guide helps you configure AWS MCP tools for AI agents. Two options are available:

OptionRequirementsCapabilities
Full AWS MCP ServerPython 3.10+, uvx, AWS credentialsExecute AWS API calls + documentation search
AWS Documentation MCPNoneDocumentation search only

Step 1: Check Existing Configuration

Before configuring, check if AWS MCP tools are already available using either method:

Method A: Check Available Tools (Recommended)

Look for these tool name patterns in your agent's available tools:

  • mcp__aws-mcp__* or mcp__aws__* → Full AWS MCP Server configured
  • mcp__*awsdocs*__aws___* → AWS Documentation MCP configured

How to check: Run /mcp command to list all active MCP servers.

Method B: Check Configuration Files

Agent tools use hierarchical configuration (precedence: local → project → user → enterprise):

ScopeFile LocationUse Case
Local.claude.json (in project)Personal/experimental
Project.mcp.json (project root)Team-shared
User~/.claude.jsonCross-project personal
EnterpriseSystem managed directoriesOrganization-wide

Check these files for mcpServers containing aws-mcp, aws, or awsdocs keys:

bash
# Check project config
cat .mcp.json 2>/dev/null | grep -E '"(aws-mcp|aws|awsdocs)"'

# Check user config
cat ~/.claude.json 2>/dev/null | grep -E '"(aws-mcp|aws|awsdocs)"'

# Or use Claude CLI
claude mcp list

If AWS MCP is already configured, no further setup needed.

Step 2: Choose Configuration Method

Automatic Detection

Run these commands to determine which option to use:

bash
# Check for uvx (requires Python 3.10+)
which uvx || echo "uvx not available"

# Check for valid AWS credentials
aws sts get-caller-identity || echo "AWS credentials not configured"

Option A: Full AWS MCP Server (Recommended)

Use when: uvx available AND AWS credentials valid

Prerequisites:

  • Python 3.10+ with uv package manager
  • AWS credentials configured (via profile, environment variables, or IAM role)

Required IAM Permissions:

json
{
  "Version": "2012-10-17",
  "Statement": [{
    "Effect": "Allow",
    "Action": [
      "aws-mcp:InvokeMCP",
      "aws-mcp:CallReadOnlyTool",
      "aws-mcp:CallReadWriteTool"
    ],
    "Resource": "*"
  }]
}

Configuration (add to your MCP settings):

json
{
  "mcpServers": {
    "aws-mcp": {
      "command": "uvx",
      "args": [
        "mcp-proxy-for-aws@latest",
        "https://aws-mcp.us-east-1.api.aws/mcp",
        "--metadata", "AWS_REGION=us-west-2"
      ]
    }
  }
}

Credential Configuration Options:

  1. AWS Profile (recommended for development):

    json
    "args": [
      "mcp-proxy-for-aws@latest",
      "https://aws-mcp.us-east-1.api.aws/mcp",
      "--profile", "my-profile",
      "--metadata", "AWS_REGION=us-west-2"
    ]
  2. Environment Variables:

    json
    "env": {
      "AWS_ACCESS_KEY_ID": "...",
      "AWS_SECRET_ACCESS_KEY": "...",
      "AWS_REGION": "us-west-2"
    }
  3. IAM Role (for EC2/ECS/Lambda): No additional config needed - uses instance credentials

Additional Options:

  • --region <region>: Override AWS region
  • --read-only: Restrict to read-only tools
  • --log-level <level>: Set logging level (debug, info, warning, error)

Reference: https://github.com/aws/mcp-proxy-for-aws

Option B: AWS Documentation MCP Server (No Auth)

Use when:

  • No Python/uvx environment
  • No AWS credentials
  • Only need documentation search (no API execution)

Configuration:

json
{
  "mcpServers": {
    "awsdocs": {
      "type": "http",
      "url": "https://knowledge-mcp.global.api.aws"
    }
  }
}

Step 3: Verification

After configuration, verify tools are available:

For Full AWS MCP:

  • Look for tools: mcp__aws-mcp__aws___search_documentation, mcp__aws-mcp__aws___call_aws

For Documentation MCP:

  • Look for tools: mcp__awsdocs__aws___search_documentation, mcp__awsdocs__aws___read_documentation

Troubleshooting

IssueCauseSolution
uvx: command not founduv not installedInstall with pip install uv or use Option B
AccessDenied errorMissing IAM permissionsAdd aws-mcp:* permissions to IAM policy
InvalidSignatureExceptionCredential issueCheck aws sts get-caller-identity
Tools not appearingMCP not startedRestart your agent after config change

Frequently asked questions

What does the Aws Mcp Setup AI skill do?

Configure AWS MCP servers for documentation search and API access. Use when setting up AWS MCP, configuring AWS documentation tools, troubleshooting MCP connectivity, or when user mentions aws-mcp, awsdocs, uvx setup, or MCP server configuration. Covers both Full AWS MCP Server (with uvx + credentials) and lightweight Documentation MCP (no auth required).

Why use Aws Mcp Setup on TypingMind?

Because you install it once and use it with any model. Aws Mcp Setup is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Mcp Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zxkane/aws-skills/tree/main/plugins/aws-common/skills/aws-mcp-setup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aws Mcp Setup?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Mcp Setup?

As many as you like. As long as a model supports skills, you can use Aws Mcp Setup with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Mcp Setup AI skill free?

Yes. It is published on GitHub by zxkane under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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