Cursor Sound MCP
Sonido del cursor MCP
Una implementación del Protocolo de Contexto de Modelo (MCP) que reproduce efectos de sonido después de que Cursor AI complete la generación de código. Este MCP se integra con Cursor para proporcionar retroalimentación de audio y ofrecer una experiencia de codificación más interactiva.
Características
Reproduce un efecto de sonido cuando el cursor completa la generación de código
Utiliza el Protocolo de Contexto de Modelo (MCP) para la integración estandarizada
Efectos de sonido configurables
Related MCP server: MCP Sound Tool
Instalación
Instalar dependencias:
npm installAñade tus efectos de sonido: Coloca tus archivos de sonido en el directorio
sounds. El sonido predeterminado esperado es:
sounds/completion.mp3- Se reproduce después de la generación del código
Puedes encontrar efectos de sonido gratuitos en freesound.org.
Construir el proyecto:
npm run buildUso
Ejecute el servidor MCP:
npm startEl servidor se iniciará y escuchará eventos del Cursor a través del transporte stdio.
Configuración
Los efectos de sonido y el volumen se pueden personalizar mediante:
Reemplazo de los archivos de sonido en el directorio
soundsModificar las rutas de los archivos de sonido en
src/index.ts
Desarrollo
Para el desarrollo con recompilación automática:
npm run devAvailable Tools
1 toolplayCompletionSoundD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- Changed
playCompletionSound1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
1 tool update
- First observed
playCompletionSound
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or confusion between tools. The single tool 'playCompletionSound' has a clear, distinct purpose that cannot be mistaken for any other tool.
With only one tool, naming consistency is inherently perfect. The tool name 'playCompletionSound' follows a clear verb_noun pattern, and there are no other tools to create inconsistency.
A single tool is generally too few for most server purposes, as it provides minimal functionality and limits agent capabilities. For a sound-related server, one tool feels thin and under-scoped, lacking operations like stop, pause, or volume control.
The tool surface is severely incomplete for a sound server. With only a 'playCompletionSound' tool, there are obvious gaps such as stopping sounds, adjusting volume, listing available sounds, or playing different types of sounds, making it inadequate for typical sound management tasks.
Maintenance
Related MCP Connectors
Audio for your agent: transcribe, speak, translate, summarise, plus sound effects and music.
Game sound effects from a text prompt: game-ready WAVs with seamless loops and variations.
UI, game and motion sound effects from a description, as a WAV and Web Audio code, named by UCS.
Generate sound effects and music from text for games, apps and videos. Returns audio file URLs.
Related MCP Servers
- AlicenseBqualityDmaintenancePlays sound effects when Cursor AI completes code generation, providing audio feedback for a more interactive coding experience.12ISC
- AlicenseAqualityFmaintenanceA Model Context Protocol implementation that plays sound effects (completion, error, notification) for Cursor AI and other MCP-compatible environments, providing audio feedback for a more interactive coding experience.31MIT
- AlicenseNot gradedqualityFmaintenanceProvides audio playback functionality for AI agents, allowing them to play notification sounds when coding tasks are completed.1MIT
- AlicenseBqualityDmaintenancePlays sound effects (completion, newtype, and error sounds) in response to various situations like task completion, insights, or errors. Integrates with Claude Desktop to provide audio feedback for improved workflow efficiency and entertainment.29 npm6MIT