"Exploring the term 'Make' or related resources" matching MCP servers:

Enables AI agents to run predefined Makefile targets as MCP tools, with configurable allow/deny lists and environment variable restrictions, without granting shell or Docker access.

Enables AI agents to execute commands in a shared tmux session that is simultaneously visible to a human via a web-based terminal UI.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

Automates Ansys Fluent simulation workflows, enabling environment checks, case execution, UDF management, and result export through MCP tools.

A production-ready MCP server that enables AI assistants to execute shell commands, manage files, monitor system resources, and automate complex workflows with advanced features like stock tracking and web automation.

Provides blocking await tools to poll commands, URLs, or files until a condition is met, eliminating the need for sleep loops in agent workflows.

An MCP server that gives coding agents hands and eyes on an Android device, providing 19 tools for building, testing, installing, UI inspection, input, logs, and toolchain diagnosis. It returns concise, structured results to make the build-debug loop efficient.

Enables cloud-based MCP clients to delegate privacy-sensitive or large-output tasks to a local LLM, returning sanitized placeholders or digested summaries so private data never leaves the user's network.

Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

Runs shell commands inside an existing microsandbox sandbox rather than on the Windows host, tracking the working directory and translating paths between the host project folder and the sandbox mount. Exposes tools for foreground or background execution with timeouts, output retrieval, killing processes, and listing them.

A Model Context Protocol server that exposes a MeshCore node and the mesh reachable through it as a clean, high-signal interface for AI agents or tools.

Make Neovim feel like Cursor. This MCP server gives an agent full control over the Neovim session it is running inside, including buffers, windows, diagnostics, LSP language intelligence, and terminals.

Bridges the OpenAI Codex CLI app-server to MCP clients, letting agents launch and resume Codex coding sessions within a chosen workspace under configurable sandbox and approval policies. It exposes tools for sending prompts, long-polling task progress and live command output, approving or canceling runtime requests, and listing or reading past session history.

MCP server that enables natural language listing, unpacking, and exporting of Unreal Engine game resources via umodel, including AES-encrypted pak support.

Bridges MCP clients to the DeepSeek API for chat completions and model discovery, with an optional locked-down bridge that delegates prompts to local CLI harnesses like Claude, Codex, or opencode.

A TypeScript MCP server template with Zod validation, dual transport (stdio/HTTP), and modular architecture for building MCP-compatible tools, resources, and prompts.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

Enables AI agents to inspect and free NVIDIA GPU VRAM by managing Ollama models, helping make room for loading new models.