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joewilsonai

GitHub MCP Server

by joewilsonai
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JavaScript
Remote

Servidor MCP de GitHub

Un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona herramientas para interactuar con la API de GitHub. Actualmente admite la creación de repositorios con descripciones, temas y URL de sitios web.

Características

  • Cree repositorios de GitHub con nombres generados automáticamente a partir de descripciones

  • Agregar temas/etiquetas a los repositorios

  • Establecer páginas de inicio del repositorio

  • Inicializar automáticamente repositorios con archivos README

Related MCP server: GitHub MCP Server

Instalación

  1. Clonar el repositorio

  2. Instalar dependencias:

npm install

  1. Construir el servidor:

npm run build

Configuración

El servidor requiere un token de acceso personal de GitHub con permisos para crear repositorios. Agregue lo siguiente a su archivo de configuración de MCP:

{
  "mcpServers": {
    "github": {
      "command": "node",
      "args": ["path/to/github-server/build/index.js"],
      "env": {
        "GITHUB_TOKEN": "your-github-token"
      }
    }
  }
}

Herramientas disponibles

crear_repositorio

Cree o actualice repositorios de GitHub utilizando comandos de lenguaje natural.

Formato de comando

La herramienta acepta comandos en lenguaje natural para diferentes operaciones:

Creando repositorios:

Create a repository for [description] with tags [tag1 tag2 tag3] website [url]

o

Make a new repository called [description] tagged with [tag1, tag2, tag3]

Actualizando la descripción del repositorio:

Update [owner/repo] description to [new description]

o

Change [repo-name] description as [new description]

Actualización de etiquetas del repositorio:

Update [owner/repo] tags to [tag1 tag2 tag3]

o

Set [repo-name] topics as [tag1, tag2, tag3]

Actualizando el sitio web del repositorio:

Update [owner/repo] website to [url]

o

Set [repo-name] homepage as [url]

Ejemplo de uso

Creando un nuevo repositorio:

const result = await use_mcp_tool({
  server_name: "github",
  tool_name: "create_repo",
  arguments: {
    command: "Create a repository for my machine learning image classifier with tags python tensorflow computer-vision website https://example.com/docs"
  }
});

Esto hará lo siguiente:

  1. Cree un repositorio llamado "my-machine-learning-image-classifier"

  2. Establezca la descripción como "mi clasificador de imágenes de aprendizaje automático".

  3. Agregue "python", "tensorflow" y "computer-vision" como temas del repositorio.

  4. Establezca el sitio web en " https://example.com/docs "

  5. Inicializar con un archivo README

Actualizando la descripción del repositorio:

const result = await use_mcp_tool({
  server_name: "github",
  tool_name: "create_repo",
  arguments: {
    command: "Update username/existing-repo description to Updated ML project for image classification"
  }
});

Actualización de etiquetas del repositorio:

const result = await use_mcp_tool({
  server_name: "github",
  tool_name: "create_repo",
  arguments: {
    command: "Update username/existing-repo tags to machine-learning python updated"
  }
});

Actualizando el sitio web del repositorio:

const result = await use_mcp_tool({
  server_name: "github",
  tool_name: "create_repo",
  arguments: {
    command: "Update username/existing-repo website to https://example.com/new-docs"
  }
});

La herramienta comprende varios patrones de lenguaje natural y palabras clave:

  • Crear/hacer/nuevo para crear repositorios

  • Actualizar/cambiar/configurar/modificar para actualizar repositorios

  • "descripción a/como" para actualizar descripciones

  • "etiquetas/temas a/como" para actualizar etiquetas

  • "sitio web/página de inicio/URL a/como" para actualizar sitios web

Desarrollo

Para modificar o ampliar el servidor:

  1. Realizar cambios en src/index.ts

  2. Reconstruir el servidor:

npm run build

Licencia

Instituto Tecnológico de Massachusetts (MIT)

Available Tools

1 tool
create_repoC

Create or update GitHub repositories using natural language commands

ParametersJSON Schema
NameRequiredDescriptionDefault
commandYesNatural language command like "Create a repository for my machine learning project with tags python tensorflow" or "Update repository-name description to New description with tags updated ml"

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool can 'create or update' repositories, implying mutation, but doesn't address permissions, rate limits, error handling, or what happens on updates (e.g., overwriting). For a mutation tool with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand quickly.

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?

Given the tool's complexity (mutation operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral traits, error conditions, or return values, which are critical for a tool that modifies GitHub repositories. The high schema coverage doesn't compensate for these gaps.

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

Parameters3/5

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

The schema description coverage is 100%, with the parameter 'command' fully documented in the schema. The description adds minimal value beyond the schema by reinforcing the natural language aspect but doesn't provide additional syntax, format details, or examples beyond what's already in the schema. This meets the baseline for high coverage.

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 tool's purpose: 'Create or update GitHub repositories using natural language commands.' It specifies the verb (create/update), resource (GitHub repositories), and method (natural language commands). However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a score of 5.

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 minimal guidance on when to use this tool. It mentions 'using natural language commands' but doesn't specify prerequisites, constraints, or when to prefer this over other methods. No explicit alternatives or exclusions are discussed, leaving usage context vague.

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. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedcreate_repo
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TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly defined as creating or updating GitHub repositories, making it distinct by default.

Naming Consistency5/5

The single tool name 'create_repo' follows a clear verb_noun pattern, and since there are no other tools to compare it to, consistency is inherently perfect. There are no deviations or mixed conventions to evaluate.

Tool Count2/5

A single tool for a GitHub server is too few for the typical scope, which usually involves multiple operations like listing repos, managing issues, or handling pull requests. This feels thin and incomplete for the domain.

Completeness2/5

The tool surface is severely incomplete for a GitHub server, as it only covers creating or updating repositories. Obvious gaps include retrieving repos, managing issues, pull requests, and other core GitHub functionalities, which will likely cause agent failures.

Maintenance

ActivityInactive
ResponsivenessSyncing

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