Using AWS Docs MCP Server for Accurate DevOps Assistance
As DevOps engineers, we constantly search for precise AWS documentation while configuring services like EC2, IAM, or Lambda. However, general-purpose AI tools often hallucinate, and navigating docs manually slows us down.
Enter the AWS Docs MCP Server — a minimal, reliable tool from AWS Labs that lets you query documentation locally with zero hallucination.
Whether you're integrating it with Amazon Q, using it inside VS Code, or embedding it into CLI tooling, this server returns direct responses from official AWS docs, fast and accurately.
What Is AWS Docs MCP Server?
The Managed Control Plane (MCP) Server is an open-source server provided by AWS Labs. It's designed to return real-time AWS documentation in response to structured requests.
It’s especially useful when paired with:
- Amazon Q Developer Agent in VS Code
- Custom CLI tools
- IDE integrations or doc-bots
Instead of relying on generative models, it gives back only what's in the AWS documentation — no more guessing.
How to Set It Up
You can configure the server using this JSON block (used in tools like Amazon Q):
"mcpServers": {
"awslabs.aws-documentation-mcp-server": {
"command": "uvx",
"args": ["awslabs.aws-documentation-mcp-server@latest"],
"env": {
"FASTMCP_LOG_LEVEL": "ERROR",
"AWS_DOCUMENTATION_PARTITION": "aws"
},
"disabled": false,
"autoApprove": []
}
}
What This Script Does
Let’s break it down:
What it does:
This script configures your system (or dev assistant like Amazon Q) to connect to the AWS Docs MCP Server, which will respond to queries using real AWS documentation.
Why we're doing it:
Because we want factual, fast, non-AI-generated answers when we ask questions about AWS services — especially for DevOps use cases like configuring IAM policies, EC2 launch templates, or CloudFormation syntax.
What output you’ll get:
Once active, this server returns structured responses like:
- The exact syntax or example for a specific AWS CLI command
- JSON or YAML config snippets from AWS docs
- Official links and metadata from AWS documentation
- Answers scoped only to actual AWS services, nothing made up
Explanation of Each Field
Field | What it Means |
---|---|
command |
Runs the MCP server using uvx (a runtime like Deno or Node). |
args |
Downloads and runs the latest version of the AWS Docs MCP Server. |
env.FASTMCP_LOG_LEVEL |
Sets log level to ERROR (suppress warnings/info logs). |
env.AWS_DOCUMENTATION_PARTITION |
Specifies that it should fetch documentation only for the public AWS partition. |
disabled |
When false , keeps the server active. |
autoApprove |
Used to control whether requests are auto-approved (leave empty for manual). |
Why It Matters for DevOps
Benefit | Description |
---|---|
No hallucination | Data is pulled directly from AWS docs — no assumptions. |
Fast | Lightweight server optimized for local/dev workflows. |
Pluggable | Easily integrates with IDEs, terminals, or dev assistants like Amazon Q. |
Expandable | AWS Labs also provides MCPs for other services (like DynamoDB, CloudWatch, etc.). |
Glossary of Terms Used
Term | Meaning |
---|---|
MCP | Managed Control Plane — a server that responds to structured dev tool queries |
Amazon Q | AWS’s AI-powered coding assistant (like Copilot or ChatGPT but AWS-specific) |
uvx | A JavaScript/TypeScript runtime used to execute MCP servers |
Partition | Refers to the AWS partition (e.g., aws , aws-cn , aws-us-gov ) |
FASTMCP | The lightweight framework powering these control plane servers |
Hallucination | When AI generates false or made-up information |
autoApprove | Controls automatic acceptance of prompts by MCP |
AWS Labs | AWS’s GitHub organization for experimental/open-source tools |
Quick Start Links
- Example Usage with Amazon Q: AWS MCP Servers
Thoughts
If you're building or maintaining AWS infrastructure, you need reliable answers fast. This tool gives you that — straight from the source.
Whether you're writing CloudFormation, troubleshooting S3 policies, or scripting with Boto3, the AWS Docs MCP Server becomes a trusted backend that supercharges your DevOps workflows.
Tried it out? Share your integrations or feedback in the comments!
Top comments (0)