"How to send OS notifications" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.

Enables interaction with ESP32/MicroPython boards via tools for flashing firmware, running REPL code, file management, and serial capture, with support for progress notifications, cancellation, and error handling.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

Enables AI assistants to interact with running games in real time — introspecting game state, simulating keyboard and mouse input to actually play, capturing screenshots, executing Lua code, hot-reloading files, and receiving push notifications when state changes.

MCP Server for the Peacock extension for VS Code (https://peacockcode.dev), coloring your world, one Code editor at a time. The main goal of the project is to show how an MCP server can be used to interact with APIs.

Enables building and shipping real apps directly from Claude or ChatGPT by scaffolding projects, editing code, running live previews with public share URLs, storing data, sending email and push notifications, deploying to hosting, and exporting finished repos.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server for integrating with various LLM clients like Claude Desktop.

Enables execution of Go code in the Go Playground sandbox and generation of shareable URLs for code snippets. Provides tools to run Go code, share code via URLs, or perform both operations simultaneously.

Exposes TypeScript Language Server Protocol functionality to AI agents, enabling them to query types at specific positions, find definitions and references, get diagnostics, run type tests, and type-check inline code just like in an IDE.

A comprehensive MCP implementation designed for fullstack development that enables code manipulation, terminal command execution, and system notifications. It provides an intelligent agent interface powered by Gemini to automate Python and Next.js development workflows.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.

An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.

A zero-data MCP server for LLM fine-tuning, providing 64 tools across 10 dimensions to prepare, build, train, evaluate, secure, package, and deliver fine-tuned models without ever accessing client data.

A demonstration MCP server that provides a simple addition tool for learning how to create and deploy servers following the Model-Context-Protocol specification. Serves as a basic example for developers getting started with MCP server development.

A vulnerable MCP server implementation that demonstrates how poor coding practices can lead to security issues like Remote Code Execution, designed for educational purposes to add numbers.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

A minimal Model Context Protocol server in TypeScript that demonstrates MCP-compliant resources and tools for LLMs, featuring simple resources and a basic tool that echoes messages or returns greetings.