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Servidor MCP de YouTube

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El servidor es un puente entre la API de YouTube y los asistentes de IA y se basa en el Protocolo de Contexto de Modelo .

Related MCP server: YouTube Tools MCP Server

¿Qué es MCP?

El Protocolo de Contexto de Modelo (MCP) es un sistema que permite que las aplicaciones de IA, como Claude Desktop, se conecten a herramientas y fuentes de datos externas. Ofrece una forma clara y segura para que los asistentes de IA trabajen con servicios y API locales, manteniendo al usuario en control.

¿Qué hace este servidor?

  • [x] Descargar subtítulos para el vídeo indicado

Casos de uso prácticos

  • [x] Crea un resumen del vídeo

Prerrequisitos

Instalación

uv tool install git+https://github.com/sparfenyuk/mcp-youtube

[!NOTA] Si ya ha instalado el servidor, puede actualizarlo utilizando el comando uv tool upgrade --reinstall .

[!NOTA] Si desea eliminar el servidor, utilice el comando uv tool uninstall mcp-youtube .

Configuración

Configuración del escritorio de Claude

Configurar Claude Desktop para reconocer el servidor MCP de YouTube.

  1. Abra el archivo de configuración de Claude Desktop:

    • En MacOS, el archivo de configuración se encuentra en ~/Library/Application Support/Claude/claude_desktop_config.json

    • En Windows, el archivo de configuración se encuentra en %APPDATA%\Claude\claude_desktop_config.json

    Nota: También puedes encontrar claude_desktop_config.json dentro de la configuración de la aplicación Claude Desktop

  2. Agregar la configuración del servidor

    {
      "mcpServers": {
        "mcp-youtube": {
            "command": "mcp-youtube",
          }
        }
      }
    }

Desarrollo

Empezando

  1. Clonar el repositorio

  2. Instalar las dependencias

    uv sync
  3. Ejecutar el servidor

    uv run mcp-youtube --help

Se pueden agregar herramientas al archivo src/mcp_youtube/tools.py .

Cómo agregar una nueva herramienta:

  1. Crea una nueva clase que herede de ToolArgs

    class NewTool(ToolArgs):
        """Description of the new tool."""
        pass

    Los atributos de la clase se usarán como argumentos para la herramienta. La cadena de documentación de la clase se usará como descripción de la herramienta.

  2. Implementar la función tool_runner para la nueva clase

    @tool_runner.register
    async def new_tool(args: NewTool) -> t.Sequence[TextContent | ImageContent | EmbeddedResource]:
        pass

    La función debe devolver una secuencia de TextContent, ImageContent o EmbeddedResource. Debe ser asíncrona y aceptar un único argumento de la nueva clase.

  3. ¡Listo! Reinicia el cliente y la nueva herramienta debería estar disponible.

La validación se puede realizar a través de Claude Desktop o ejecutando la herramienta directamente.

Depuración del servidor en el Inspector

El inspector MCP es una herramienta que ayuda a depurar el servidor mediante una interfaz de usuario sofisticada. Para ejecutarlo, use el siguiente comando:

npx @modelcontextprotocol/inspector uv run mcp-youtube

Solución de problemas

Mensaje 'No se pudo conectar al servidor MCP mcp-youtube'

Si ve el mensaje 'No se pudo conectar al servidor MCP mcp-youtube' en Claude Desktop, significa que la configuración del servidor es incorrecta.

Pruebe lo siguiente:

  • Utilice la ruta completa al binario mcp-youtube en el archivo de configuración

Available Tools

1 tool
DownloadClosedCaptionsC

Download closed captions from YouTube video.

ParametersJSON Schema
NameRequiredDescriptionDefault
video_urlYes

TDQS

C2.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'download' implies a read operation, it doesn't specify authentication requirements, rate limits, output format, error conditions, or whether it modifies any state. This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at just one sentence with no wasted words. It's front-loaded with the core purpose and contains no unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations, no output schema, and 0% schema description coverage, the description is insufficient. It doesn't explain what format the captions are returned in, whether authentication is needed, or any error handling. The minimal description leaves too many questions unanswered for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, and the description doesn't provide any information about the single parameter beyond what's implied by the tool name. No details about the video_url format, validation rules, or examples are given, leaving the parameter poorly documented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('download') and resource ('closed captions from YouTube video'), making the purpose immediately understandable. However, with no sibling tools mentioned, there's no opportunity to differentiate from alternatives, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or limitations. It simply states what the tool does without contextual usage information.

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. 1 tool updatev1.0.0
    • AddedDownloadClosedCaptions

TDQS

C2.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool has a single, clear purpose that is distinct by default.

Naming Consistency5/5

The single tool name follows a clear verb_noun pattern (DownloadClosedCaptions), and with no other tools, consistency is inherently perfect. There are no deviations or mixed conventions to evaluate.

Tool Count2/5

A single tool for a YouTube server is too few for the apparent scope, as YouTube involves many operations like searching videos, getting metadata, or managing playlists. This feels thin and incomplete for the domain.

Completeness1/5

The tool surface is severely incomplete for a YouTube server. It only covers downloading closed captions, with no support for core YouTube functionalities such as video search, retrieval, or interaction, leading to significant gaps and agent failures.

Maintenance

ActivityInactive
ResponsivenessNo issues

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