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aws-mcp-servers.mcp

AWS MCP Servers

AWS Labs' official collection of 80+ MCP servers, one per AWS service area (documentation, IaC, databases, serverless, cost, observability), each installable independently via uvx or Docker.

Overview

AWS MCP Servers is the open source collection maintained by AWS Labs to connect coding agents to real AWS documentation, pricing and service APIs instead of relying on a model's training data, which is often out of date for a fast-moving cloud platform.

How it works

  1. The repository is organized as one server per AWS service or workflow area: documentation, CloudFormation/CDK, DynamoDB, Aurora, ElastiCache, Lambda, ECS/EKS, Bedrock, CloudWatch, pricing and dozens more, each in its own src/ folder with its own README.
  2. Every server is installed and run independently through uvx, so an agent only pulls in the servers relevant to what it's doing rather than one large, all-purpose tool.
  3. Servers run locally by default, using your own AWS credentials, but several (like AWS Knowledge and the in-preview AWS MCP Server) are also offered as fully managed, remote servers hosted by AWS.
  4. AWS Labs also publishes Docker images for each server in a public ECR registry, for teams that prefer running these in containers over uvx.
  5. As of mid-2026, AWS is migrating the most-used servers here into a successor product called Agent Toolkit for AWS, aimed at production agent workloads; this repository keeps working and accepting contributions in the meantime.

Examples

"Use the Terraform MCP server and the AWS Pricing MCP server to estimate
the monthly cost of this CDK stack before I deploy it."

Installation

You need uv (for uvx) or Docker, valid AWS credentials configured locally, and an MCP client such as VS Code, Claude Code/Desktop or Cursor.

  1. Install uv if you don't have it, or use AWS Labs' Docker images from its public ECR registry instead.
  2. Configure AWS credentials locally (aws configure, or environment variables) so the server can call real AWS APIs on your behalf.
  3. Pick the server you need, for example the AWS Documentation server, and add its config block (see the sidebar) to your MCP client.
  4. Restart your client and confirm the new tools appear.
  5. Repeat step 3 for any other AWS service server you want; each one installs and runs independently.

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