"Setting up an MCP server in Kubernetes" matching MCP servers:

An MCP wrapper for Up Bank's API that allows Claude and other MCP-enabled clients to manage accounts, transactions, categories, tags, and webhooks from Up Bank.

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 agents to create, edit, and share collaborative markdown documents hosted on the user's own Cloudflare account, with ordered writes and live updates to open editors.

MCP server that gives AI assistants full access to Kubernetes clusters and Helm, exposing 73 tools for managing pods, deployments, services, configs, secrets, logs, exec, port-forwarding, Helm lifecycle, and more.

Manages Kubernetes clusters through kubectl and Helm operations including pod cleanup, node management, and troubleshooting.

Publishes a spending-summary tool alongside an interactive HTML view, letting people click a category in the answer to fetch the individual expense records behind that total. Keeps calculations and their supporting evidence together in a single inspectable flow.

Enables secure Kubernetes operations with configurable security modes, supporting core Kubernetes resources, Istio service mesh, and Helm chart management through natural language.

Enables MCP clients to interact with Up Bank accounts and transactions, including reading balances, summarizing spending, and categorizing or tagging transactions.

Enables comprehensive Kubernetes cluster management through kubectl operations and Helm chart management. Supports resource operations, logging, scaling, rollouts, and diagnostics with multiple transport modes and security features.

MCP server for amazon.in — cheapest in-stock, best-value picks, and price history links.

Provides access to Kubernetes troubleshooting runbooks, enabling search, discovery, and retrieval of guides for common issues like pod crashes, node problems, and network failures.

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

Enables integration with Up Banking API to query account balances, transaction history, and spending categories. Supports filtering transactions by date, category, tags, and account type for comprehensive banking insights.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

An MCP server that gives AI agents full access to Follow Up Boss CRM via natural language, enabling CRUD operations on people, deals, appointments, and more through 160 tools.

Enables Claude to interact with Follow Up Boss CRM, allowing lead management, task scheduling, and pipeline tracking through natural language.

An MCP server that connects AI assistants to YNAB budgets, enabling natural language queries about finances backed by full API coverage and built-in YNAB methodology knowledge.

Enables Indian bank branch IFSC code lookup via Razorpay's open API, allowing AI agents to retrieve branch details using IFSC codes.

Enables users to describe an LLM fine-tuning workload and receive ranked, cost- and runtime-optimized GPU recommendations across multiple cloud providers by estimating VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job once and receive the cheapest, fastest, or most balanced GPU hardware options across a dozen cloud providers by calculating required VRAM/FLOPs and aggregating live pricing.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning workload once and get task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, and balanced GPU recommendations across multiple cloud providers.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning workload once and get ranked, cost- and speed-optimized GPU recommendations across multiple cloud providers by estimating VRAM/FLOPs requirements.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and automatically estimates required VRAM/FLOPs, compares live GPU pricing across cloud providers, and returns ranked cheapest, fastest, or balanced hardware recommendations.

Enables users to describe an LLM fine-tuning workload and receive ranked, task-aware GPU recommendations by estimating required VRAM/FLOPs and comparing live pricing across a dozen cloud providers.

Enables users to describe an LLM fine-tuning job once and receive ranked GPU recommendations across many cloud providers based on estimated VRAM/FLOPs, cost, and runtime.

Enables users to describe an LLM fine-tuning job in natural language and receive ranked GPU recommendations from a dozen cloud providers, based on estimated VRAM and FLOPs requirements. It surfaces the cheapest, fastest, and most balanced hardware options while disclosing the source and freshness of each price.