"Fetching Kubernetes logs for a given pod or deployment" matching MCP servers:

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

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.

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.

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

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

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.

Provides deterministic tools and resources for order-to-cash deployment, enabling payment investigation, collection prioritization, and controlled benchmark runs on synthetic ERP data.

MCP server for Python JSON logs

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 over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

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

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

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 LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.