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Amazon EKS MCP Server

Official AWS Labs MCP server for Amazon EKS that gives AI code assistants real-time cluster state visibility and Kubernetes/EKS resource management, from cluster setup through deployment, troubleshooting, and optimization.

by AWS Labs·added 2026-06-21·
HarnessClaude CodeCodexCursorClaude Desktop
Review first review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Source URLs
https://github.com/awslabs/mcp/blob/main/src/eks-mcp-server/README.md, https://github.com/awslabs/mcp, https://awslabs.github.io/mcp/
Brand
AWS Labs
Brand domain
aws.amazon.com
Brand asset source
brandfetch
Safety notes
The configuration above is read-only. Adding the `--allow-write` flag lets the server create, update, patch, and delete EKS/Kubernetes resources (including creating clusters via CloudFormation) and `--allow-sensitive-data-access` exposes logs and events; enable these only deliberately., This server acts on real infrastructure with your AWS credentials; scope the profile to the intended account, region, and clusters, and prefer non-production targets while evaluating it., Run it only on a trusted host, and review any generated manifests or CloudFormation actions before applying them.
Privacy notes
Cluster state, resource manifests, ARNs, and account/region metadata can be returned through tool calls and exposed to the model., With sensitive-data access enabled, pod logs and Kubernetes events may be returned; keep account identifiers, credentials, and log contents out of public prompts, issues, and screenshots.
Author
AWS Labs
Submitted by
jaso0n0818
Claim status
unclaimed
Last verified
2026-06-21

Safety notes

  • The configuration above is read-only. Adding the `--allow-write` flag lets the server create, update, patch, and delete EKS/Kubernetes resources (including creating clusters via CloudFormation) and `--allow-sensitive-data-access` exposes logs and events; enable these only deliberately.
  • This server acts on real infrastructure with your AWS credentials; scope the profile to the intended account, region, and clusters, and prefer non-production targets while evaluating it.
  • Run it only on a trusted host, and review any generated manifests or CloudFormation actions before applying them.

Privacy notes

  • Cluster state, resource manifests, ARNs, and account/region metadata can be returned through tool calls and exposed to the model.
  • With sensitive-data access enabled, pod logs and Kubernetes events may be returned; keep account identifiers, credentials, and log contents out of public prompts, issues, and screenshots.

Prerequisites

  • An AWS account with Amazon EKS and permissions to view (and, if enabled, manage) the target clusters.
  • Python 3.10 or newer and `uv` / `uvx` installed (Astral) to run the package.
  • AWS credentials configured locally (for example via `aws configure` or `AWS_PROFILE`) scoped to the intended account, region, and clusters.
  • An MCP client that supports stdio servers; the server runs locally on the same host as the client.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
15 minutes
Difficulty
advanced
Tool listing metadata
Pricing
open-source
Disclosure
editorial
Application category
DeveloperApplication
Operating system
Cross-platform
Full copyable content
{
  "awslabs.eks-mcp-server": {
    "command": "uvx",
    "args": ["awslabs.eks-mcp-server@latest"],
    "env": {
      "AWS_PROFILE": "${AWS_PROFILE}",
      "AWS_REGION": "us-east-1",
      "FASTMCP_LOG_LEVEL": "ERROR"
    }
  }
}

About this resource

Overview

Amazon EKS MCP Server is an official AWS Labs Model Context Protocol server that gives AI code assistants real-time visibility into Amazon EKS clusters and tools to manage Kubernetes resources. It spans the lifecycle — from cluster setup with sane defaults, through application deployment and resource management, to log/event retrieval and troubleshooting — all through natural-language interactions.

It runs locally over stdio via uvx from the published awslabs.eks-mcp-server Python package and uses your local AWS credentials. The configuration shown is read-only; write and sensitive-data access are opt-in flags.

Features

  • Cluster setup — create EKS clusters with prerequisites (VPC, networking, Auto Mode node pools) via CloudFormation (write mode).
  • Application deployment — apply existing Kubernetes YAML or generate deployment/service manifests from parameters (write mode).
  • Resource lifecycle — create, read, update, patch, and delete Kubernetes resources such as Pods, Services, and Deployments (write mode).
  • Discovery — list Kubernetes resources filtered by namespace, labels, and fields for state awareness.
  • Operations — retrieve pod/container logs and Kubernetes events for troubleshooting and monitoring (sensitive-data mode).

Use Cases

  • Inspect the live state of an EKS cluster and its Kubernetes resources.
  • Troubleshoot a failing workload by pulling its logs and related events.
  • Generate and apply Kubernetes manifests for a new deployment (write mode).
  • Stand up a new EKS cluster with best-practice defaults (write mode).

Installation

Claude Code

  1. Install Python 3.10+ and uv.
  2. Configure an AWS profile and region scoped to the target EKS clusters.
  3. Add the server with the read-only stdio configuration above. To enable mutations, append --allow-write (and --allow-sensitive-data-access for logs/events) to args — only when you intend those operations.
  4. Verify it is connected with claude mcp list.

Claude Desktop / Cursor / Kiro / VS Code

Add the configSnippet above to your client's MCP configuration and set AWS_PROFILE/AWS_REGION. The first run downloads the package via uvx.

Source And Trust

This entry is based on the official AWS Labs awslabs/mcp repository and the published PyPI package (Apache-2.0). The server can act on real EKS/Kubernetes infrastructure when write access is enabled, so scope credentials tightly, keep write/sensitive-data flags opt-in, and verify the configuration against the linked source before using it in automated workflows.

Source citations

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BrandAWS Labs logoAWS LabsAWS Labs logoAWS LabsAWS Labs logoAWS LabsAWS Labs logoAWS Labs
Categorymcpmcpmcpmcp
Sourcesource-backedsource-backedsource-backedsource-backed
AuthorAWS LabsAWS LabsAWS LabsAWS Labs
Added2026-06-212026-06-212026-06-212026-06-21
Platforms
Claude CodeCodexCursorClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Source repo
Safety notesThe configuration above is read-only. Adding the `--allow-write` flag lets the server create, update, patch, and delete EKS/Kubernetes resources (including creating clusters via CloudFormation) and `--allow-sensitive-data-access` exposes logs and events; enable these only deliberately. This server acts on real infrastructure with your AWS credentials; scope the profile to the intended account, region, and clusters, and prefer non-production targets while evaluating it. Run it only on a trusted host, and review any generated manifests or CloudFormation actions before applying them.The configuration above is read-only. Setting `ALLOW_WRITE=true` lets the server create and modify infrastructure (ECR repos, CloudFormation stacks, ECS services) and `ALLOW_SENSITIVE_DATA=true` exposes logs; enable these only deliberately. AWS documents this server as primarily for development, testing, and non-critical environments; keep write/sensitive-data disabled for production accounts and prefer non-production targets while evaluating it. This server acts on real infrastructure with your AWS credentials; scope the profile to the intended account, region, and resources, and run it only on a trusted host.This server calls Amazon Location Service place and route APIs with your AWS credentials; scope the profile to Location Service access and the intended account and region. The tools are query-oriented (search, geocode, route) rather than resource-mutating, but Amazon Location Service API calls may incur AWS usage costs. Run it only on a trusted host, since it uses the local machine's AWS credentials to reach your account.Resource creation/deletion is gated by the `--allow-resource-creation` flag (default off); without it, create/delete tools are hidden. Enable it only deliberately, and grant `AmazonSNSFullAccess`/`AmazonSQSFullAccess` only when you intend mutations. The server tags resources it creates and will only modify resources carrying that tag, which prevents it from changing pre-existing topics/queues it did not create. This server acts on real messaging infrastructure with your AWS credentials; scope the profile to the intended account and region and run it only on a trusted host.
Privacy notesCluster state, resource manifests, ARNs, and account/region metadata can be returned through tool calls and exposed to the model. With sensitive-data access enabled, pod logs and Kubernetes events may be returned; keep account identifiers, credentials, and log contents out of public prompts, issues, and screenshots.Cluster, service, task, task-definition, and ECR metadata plus account/region identifiers can be returned through tool calls and exposed to the model. With sensitive-data access enabled, logs and deployment details may be returned; keep account identifiers, credentials, and log contents out of public prompts, issues, and screenshots.Place queries, coordinates, addresses, and waypoints you ask about are sent to Amazon Location Service using your configured credentials. Returned place details, addresses, and route geometry are exposed to the model; keep account identifiers and credentials out of public prompts, issues, and screenshots.Topic/queue names, ARNs, subscription details, and account/region metadata can be returned through tool calls and exposed to the model. Message send/receive tools can read and write message payloads; keep sensitive message contents, account identifiers, and credentials out of public prompts, issues, and screenshots.
Prerequisites
  • An AWS account with Amazon EKS and permissions to view (and, if enabled, manage) the target clusters.
  • Python 3.10 or newer and `uv` / `uvx` installed (Astral) to run the package.
  • AWS credentials configured locally (for example via `aws configure` or `AWS_PROFILE`) scoped to the intended account, region, and clusters.
  • An MCP client that supports stdio servers; the server runs locally on the same host as the client.
  • An AWS account with Amazon ECS/ECR and permissions to view (and, if enabled, deploy) the target resources.
  • Docker or Finch for containerization and local image builds.
  • Python 3.10 or newer and `uv` / `uvx` installed (Astral) to run the package.
  • AWS credentials configured locally (for example via `aws configure` or `AWS_PROFILE`) scoped to the intended account, region, and resources.
  • An AWS account with Amazon Location Service enabled in your chosen region.
  • Python 3.10 or newer and `uv` / `uvx` installed (Astral) to run the package.
  • AWS credentials configured locally (for example via `aws configure` or `AWS_PROFILE`) with permissions for Amazon Location Service place and route APIs.
  • An MCP client that supports stdio servers; the server runs locally on the same host as the client.
  • An AWS account with Amazon SNS and SQS, and permissions for the topics/queues you intend to inspect or manage.
  • Python 3.10 or newer and `uv` / `uvx` installed (Astral) to run the package.
  • AWS credentials configured locally (for example via `aws configure` or `AWS_PROFILE`); AWS recommends a least-privilege role with `AmazonSNSReadOnlyAccess` and `AmazonSQSReadOnlyAccess`.
  • An MCP client that supports stdio servers; the server runs locally on the same host as the client.
Install
uvx awslabs.eks-mcp-server@latest
uvx --from awslabs-ecs-mcp-server ecs-mcp-server
uvx awslabs.aws-location-mcp-server@latest
uvx awslabs.amazon-sns-sqs-mcp-server@latest
Config
{
  "mcpServers": {
    "awslabs.eks-mcp-server": {
      "command": "uvx",
      "args": ["awslabs.eks-mcp-server@latest"],
      "env": {
        "AWS_PROFILE": "${AWS_PROFILE}",
        "AWS_REGION": "us-east-1",
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "awslabs.ecs-mcp-server": {
      "command": "uvx",
      "args": ["--from", "awslabs-ecs-mcp-server", "ecs-mcp-server"],
      "env": {
        "AWS_PROFILE": "${AWS_PROFILE}",
        "AWS_REGION": "us-east-1",
        "FASTMCP_LOG_LEVEL": "ERROR",
        "ALLOW_WRITE": "false",
        "ALLOW_SENSITIVE_DATA": "false"
      },
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "awslabs.aws-location-mcp-server": {
      "command": "uvx",
      "args": ["awslabs.aws-location-mcp-server@latest"],
      "env": {
        "AWS_PROFILE": "${AWS_PROFILE}",
        "AWS_REGION": "us-east-1",
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "awslabs.amazon-sns-sqs-mcp-server": {
      "command": "uvx",
      "args": ["awslabs.amazon-sns-sqs-mcp-server@latest"],
      "env": {
        "AWS_PROFILE": "${AWS_PROFILE}",
        "AWS_REGION": "us-east-1",
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "type": "stdio"
    }
  }
}
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