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Ismail Kovvuru
Ismail Kovvuru

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AWS Docs MCP Server for DevOps Assistance

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": []
  }
}
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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

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!

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