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

Persistent memory and pattern learning for AI coding assistants via MCP.

An MCP server that enables interaction with Kubernetes resources through natural language interfaces like Goose CLI, allowing users to get, read, and patch Kubernetes resources.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

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 agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK, with examples of tools (calculator, greeting) and resources (server info).

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

Enables AI assistants to run, list, and analyze Lupa test suites, returning structured JSON results for debugging.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

Allows LLMs to execute Wolfram Language code in a secure, session-based environment by providing an interface to interact with a Wolfram Mathematica kernel.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

An MCP bridge that lets Codex supervise Reasonix as an implementation worker in an isolated Git worktree, ensuring safe delegation with scoped writes and sandboxed execution.

Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.

Enables AI agents to interact with Bentley STAAD.Pro models for tasks like load case definition, data extraction, and property setting through natural language.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

Enables any LLM to drive your local Codex CLI in a sandboxed workspace, running coding tasks and generating images without needing an API key.

An MCP server that manages an IPython kernel, allowing LLMs to execute Python code in a project's virtual environment.

Speeds up coding agents by predicting and pre-executing upcoming tool calls, then safely returning validated cached results to eliminate wait time.

An MCP server that provides tools for getting second opinions or detailed code reviews from Gemini 2.5 Pro by embedding file contents in prompts, allowing it to handle large codebases with extensive context.

Enables execution of TypeScript code to call MCP tools instead of direct tool calls, reducing token usage by up to 98% while orchestrating complex multi-tool workflows through secure sandboxed code execution.

Read-only MCP server for safe Kubernetes inspection, diagnosis, and debugging. Supports Kubernetes core, Helm, Argo Workflows, and Argo CD.

Enables an LLM to orchestrate multiple downstream MCP tools inside one isolated sandbox in a single turn, filtering intermediate results in memory and returning only the final output to cut context tokens.

Enables AI coding agents to run Kubernetes inspection and Terraform plan/apply operations inside ephemeral gVisor-sandboxed jobs with short-lived, narrowly-scoped credentials, while routing destructive changes through a human approval gate.

An MCP server for bridging your local agent to a Colab session in the browser.

An MCP server that enables processing of massive datasets up to 10M+ tokens using a recursive language model pattern for strategic chunking and analysis. It automates sub-queries and result aggregation using free local inference via Ollama or the Claude API to handle context beyond standard prompt limits.

An MCP server for self-hosted Overleaf Community Edition that lets coding agents create projects, write LaTeX, compile, and receive structured diagnostics while humans edit the same document in the browser.

An MCP server for Roblox that provides tools to execute Luau code, inspect and modify game instances, teleport players, fire remote events, and stream client logs in real-time via a web dashboard.

Enables MCP-compatible AI agents to access Polymarket prediction-market data and run Python 3.12 in an isolated sandbox, with each call paid automatically in USDC on Base.

Allows executing shell commands within a secure Docker container through Claude's MCP interface, providing Kubernetes tools and isolated environment without host Docker daemon access.

An MCP server that enables AI agents to interact with Modal, allowing them to deploy apps and run functions in a serverless cloud environment.