AWS MCP Setup
AWS documentation and MCP setup skill for configuring AWS knowledge tools, credentials, and connectivity in Claude workflows.
What this skill does
Connect your AI assistant to AWS securely without handling the complex setup yourself. You will gain the ability to search official documentation or manage cloud resources directly within your chat conversations. Use this whenever you need to enable AWS tools for your workflow or fix broken connections between your assistant and cloud account.
name: aws-mcp-setup description: 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). allowed-tools:
- Bash(which *)
- Bash(aws sts get-caller-identity*)
- Bash(claude mcp *)
- Bash(cat mcp.json)
- Bash(cat claude.json)
AWS MCP Server Configuration Guide
Overview
This guide helps you configure AWS MCP tools for AI agents. Two options are available:
| Option | Requirements | Capabilities |
|---|---|---|
| Full AWS MCP Server | Python 3.10+, uvx, AWS credentials | Execute AWS API calls + documentation search |
| AWS Documentation MCP | None | Documentation 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__*ormcp__aws__*→ Full AWS MCP Server configuredmcp__*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):
| Scope | File Location | Use Case |
|---|---|---|
| Local | .claude.json (in project) | Personal/experimental |
| Project | .mcp.json (project root) | Team-shared |
| User | ~/.claude.json | Cross-project personal |
| Enterprise | System managed directories | Organization-wide |
Check these files for mcpServers containing aws-mcp, aws, or awsdocs keys:
# 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:
# 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
uvpackage manager - AWS credentials configured (via profile, environment variables, or IAM role)
Required IAM Permissions:
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Action": [
"aws-mcp:InvokeMCP",
"aws-mcp:CallReadOnlyTool",
"aws-mcp:CallReadWriteTool"
],
"Resource": "*"
}]
}
Configuration (add to your MCP settings):
{
"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:
-
AWS Profile (recommended for development):
"args": [ "mcp-proxy-for-aws@latest", "https://aws-mcp.us-east-1.api.aws/mcp", "--profile", "my-profile", "--metadata", "AWS_REGION=us-west-2" ] -
Environment Variables:
"env": { "AWS_ACCESS_KEY_ID": "...", "AWS_SECRET_ACCESS_KEY": "...", "AWS_REGION": "us-west-2" } -
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:
{
"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
| Issue | Cause | Solution |
|---|---|---|
uvx: command not found | uv not installed | Install with pip install uv or use Option B |
AccessDenied error | Missing IAM permissions | Add aws-mcp:* permissions to IAM policy |
InvalidSignatureException | Credential issue | Check aws sts get-caller-identity |
| Tools not appearing | MCP not started | Restart your agent after config change |
Install this Skill
Skills give your AI agent a consistent, structured approach to this task — better output than a one-off prompt.
npx skills add zxkane/aws-skills --skill plugins/aws-common Community skill by @zxkane. Need a walkthrough? See the install guide →
Details
- Category
- Development
- License
- MIT
- Author
- @zxkane
- Source
- GitHub →
- Source file
-
show path
plugins/aws-common/skills/aws-mcp-setup/SKILL.md
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