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

Small production-oriented MCP server for diagnosing incidents from Elasticsearch logs with unknown schema. It provides tools for log discovery, retrieval, and issue diagnosis.

A read-only MCP server that gives AI assistants natural language access to Elasticsearch/Kibana logs for querying and analysis.

A Model Context Protocol (MCP) server that provides safe, read-only access to Kubernetes resources for debugging and inspection. Built with security in mind, it offers comprehensive cluster visibility without modification capabilities.

Enables safe, read-only interaction with Kubernetes clusters, allowing users to list resources and fetch logs without any create/update/delete operations.

Enables diagnosing Kubernetes clusters without creating or changing cluster objects, with tools to inspect health, workloads, events, storage, RBAC, custom resources, logs, and configuration.

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 Claude Desktop to interact with 57 AWS services using over 200 tools and local machine profiles. It supports multi-profile configurations and features a read-only safe mode by default to manage infrastructure like EC2, S3, and Lambda securely.

A read-only Model Context Protocol server that exposes over 60 AWS tools across services like EC2, S3, and IAM for AI agent interaction. It features multi-region support, resource caching, and audit logging to provide secure, AI-ready access to AWS infrastructure data.

A read-only MCP server that exposes tools to query Datadog monitors and logs, and AWS CloudWatch Logs, and to group recurring errors by fingerprint. Designed for use with Claude Code to diagnose issues and propose fixes.

Enables AI assistants to troubleshoot AWS and hybrid network connectivity by analyzing hop-by-hop paths across security groups, NACLs, route tables, Transit Gateway routes, VPN/BGP, DNS, and flow logs to identify blocking rules and suggest fixes.

Enables advanced management of Kubernetes clusters through natural language interactions. Supports querying, managing, and monitoring pods, deployments, nodes, and logs across multiple contexts and namespaces.

A read-only MCP server for safe, structured investigation of AWS serverless resources, providing curated tools for tracing dependencies, permissions, and failures without exposing raw SDK access.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

Enables LLM clients to query AWS CloudWatch Logs and Alarms through MCP tools.

A read-only MCP server that lets an AI assistant inspect a single AWS lab instance's EC2 health, recent system/nginx errors from CloudWatch, and nginx service status via SSM, with strict allowlisting and no generic shell access.

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.

A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.

Enables secure tool discovery and execution on AWS Lambda with role-based access control, command injection defense, and sensitive data redaction, allowing managed CloudWatch log queries and Terraform operations through a standard MCP interface.

Enables natural language Kubernetes cluster operations, SLO monitoring, and PromQL queries via Claude using the Model Context Protocol.

Enables real-time Kubernetes cluster observability and debugging through standardized MCP interface. Provides access to pods, services, nodes, events, and includes built-in tools for cluster health analysis and issue identification.

Enables interactive Kubernetes cluster monitoring and troubleshooting through natural language queries. Users can diagnose pod issues, check service status, and investigate cluster problems using conversational AI.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

Enables AI agents to diagnose and analyze AWS serverless infrastructure through Model Context Protocol, providing access to CloudWatch logs, Lambda functions, DynamoDB tables, IAM policies, and Bedrock-powered incident root-cause analysis.

Exposes Kubernetes cluster state with specialized telecom awareness of 5G Core network functions and topologies to MCP-compatible LLMs. It enables natural language analysis of 5G workloads, network slices, UPF data planes, and cluster health.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Model Context Protocol (MCP) server for debugging, analyzing, and diagnosing Kubernetes clusters directly from AI agents.

Enables agents to autonomously investigate deployment health by inspecting Kubernetes resources, comparing live cluster state against Git, and correlating findings with Dynatrace problems.

Sigma detection rule writing, validation, and pySigma-based multi-backend conversion (Splunk, Elastic, Wazuh, Kibana) via 3 MCP tools and 3 Claude Code skills, backed by a 61-rule production corpus across 11 MITRE ATT\&CK tactic categories.