"Software Development Lifecycle Guide and Resources" matching MCP servers:

Enables LLMs to list, open, and close installed software on Windows, macOS, and Linux through natural language.

Centralized MCP server that provides standardized development workflow commands to Cursor AI, auto-detecting project type (Laravel, Next.js, Flutter, Architecture) and offering relevant commands for implementation, testing, and commits.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

Combines KC Chat Panel session interaction with AgentDock computer control tools, enabling Cursor Cloud Agent to chat and operate the local machine via AgentDock.

Wraps another MCP server to allow lifecycle management (start/stop/restart) and proxy its tools, resources, and notifications, enabling iterative development without agent reconnection.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

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.

Enables agents to launch and control interactive terminal sessions, inspecting screen text and formatting while sending keyboard and mouse input. Supports real pseudoterminals with resizing, snapshots, and session lifecycle management.

Cognitive security for AI-assisted development, preventing dangerous commands and large AI code rewrites when fatigued.

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.

MCP server for TQS structural engineering CAD/analysis software, enabling Claude to read building models, extract drawing data, run structural processing, and script against the TQS API.

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

Advanced shell command execution for AI agents — a Model Context Protocol (MCP) server with security policy engine, process lifecycle management, bounded output capture, POSIX signals, and token-efficient responses.

MCP server that gives AI coding agents hands, eyes and a mechanic's ear for React Native development.

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

A MCP server that enables human-in-the-loop workflow in AI-assisted development tools by allowing users to run commands, view their output, and provide textual feedback directly to the AI assistant.

An MCP server that enables AI agents to list and run tasks defined in Taskfile.yml, useful for automated development workflows.

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

Acts as the 'Hands and Eyes' for an Autonomous AI Agent, bridging Large Language Models and your local development environment to enable safe file manipulation, context reading, command execution, and documentation verification.