"Managing Kubernetes Clusters on AWS Elastic Beanstalk" matching MCP servers:

Connects to Elasticsearch clusters through the Model Context Protocol, enabling natural language querying and management of Elasticsearch data. Provides tools to search indices, list available indices, and retrieve index mappings.

Enables MCP clients to inspect and operate Kubernetes clusters across multiple contexts, with read-only/read-write/admin access modes and security flags controlling namespaces, contexts, deletes, applies, and exec.

Enables AI assistants to interact with Kubernetes clusters through 50 specialized tools for comprehensive cluster management. Supports both local kubectl and remote SSH-based execution for managing pods, deployments, services, and other Kubernetes resources.

Provides read-only access to Kubernetes clusters for AI assistants.

Enables connecting to a Kubernetes cluster to manage resources and troubleshoot workloads with kubectl and Helm operations, including logs, scaling, port forwarding, and non-destructive mode.

Enterprise-grade MCP server for Kubernetes operations, supporting local kubeconfig and AWS EKS authentication, with read, write, and destructive operations protected by multi-layer safety guards.

An Elasticsearch-based AI memory system optimized for Chinese that enables persistent knowledge storage and complex entity relationship management via the Model Context Protocol. It features advanced semantic search using the IK analyzer and supports multi-zone memory isolation for specialized knowledge graphs.

A powerful and flexible Kubernetes MCP server implementation with support for OpenShift.

An MCP server that enables AI assistants to interact with Kubernetes clusters by translating natural language into kubectl and Helm operations. It allows users to query, manage, and diagnose Kubernetes resources and cluster states through a seamless integration.

MCP server for automated AWS security scanning — 19 modules, risk scoring, zero write operations.

Enables AI assistants to manage Docker containers and Kubernetes resources through natural language, supporting operations like container management, image building, and pod/deployment/service management.

An MCP server that gives AI assistants direct access to Kubernetes clusters for pod management and network debugging (DNS, NetworkPolicy, ingress, service mesh) and correlates Dynatrace observability with OpenTelemetry self-monitoring, which automatically ships traces, metrics, and logs to Dynatrace.

Enables management and provisioning of AWS resources like EC2, S3, and RDS using natural language prompts through the Model Context Protocol. It allows users to automate complex infrastructure tasks, such as setting up VPCs and security groups, via a chat interface.

A Model Context Protocol server allowing Claude AI to interact with AWS resources through natural language, enabling users to query and manage AWS services without using the traditional AWS Console or CLI.

A unified MCP server for AWS that enables natural language infrastructure management, cross-service resource discovery, and dependency mapping. It features 30 intelligent tools for cost optimization, incident investigation, and multi-account operations protected by a robust safety system.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Enables running a stateless Streamable HTTP MCP server on AWS Lambda behind API Gateway with JWT bearer authentication, per-scope tool allowlists, OAuth protected-resource metadata, and a CDK construct for deployment.

An MCP server that exposes AWS EC2 pricing data with an option to search by CPU, RAM, networking

This server implements the Multi-Agent Conversation Protocol for AWS SecurityHub, enabling interaction with AWS SecurityHub API through natural language commands.

Enables users to generate professional AWS architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python code through the diagrams package. Supports customizable styling and secure diagram generation for cloud infrastructure visualization.

Enables Claude to interact with core AWS services like S3, EC2, RDS, and CloudWatch, along with a generic SDK wrapper for any AWS operation. It also supports cost monitoring and optional vector store capabilities for document ingestion and search.

Enables evidence-first AWS architecture work through deterministic design calculations, live official AWS knowledge, integration catalog/configuration, and optional authenticated local read-only AWS tooling for requirements, comparisons, diagrams, ADRs, and operational planning.

A server that enables LLMs to manage Kubernetes clusters through natural language commands, wrapping kubectl operations to provide a simplified interface for common Kubernetes tasks.

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

Enables analyzing AWS cloud spending and Bedrock usage through natural language queries using Claude.

A command-line interface and API that allows users to analyze and visualize AWS cloud spending data by enabling Claude to query AWS Cost Explorer through natural language conversations.

Enables read-only assessment of AWS environments by inventorying resources, running security and operational checks, and generating actionable reports with cost analysis. Designed for contractors with support for assume-role authentication using external IDs.

Automates the AWS Foundational Technical Review (FTR) partner self-assessment by evaluating SOC 2 and WAFR reports against defined controls, returning structured PASS/FAIL decisions with reasoning.

Enables Claude to create, list, inspect, and delete custom rowing workouts in the EXR indoor rowing app, converting intervals.icu workout documents (power, cadence, ramps, repeats) into EXR's simpler timed or distance-based blocks with dates in the titles. Runs as an AWS Lambda-hosted claude.ai custom connector with per-user OAuth sign-in, so several people can share one deployment while each only sees their own EXR workouts.

Enables Claude and other AI agents to read sleep and recovery data from a Fitbit or Pixel Watch through the Google Health API, including HRV, resting and sleeping heart rate, SpO2, breathing rate, skin temperature, and detailed sleep stages compared against a personal baseline. It runs as a shared AWS Lambda custom connector with per-user Google sign-in and read-only tools for recovery status, daily metrics, sleep sessions, and night-level detail.