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erm-github-mcp

erm-github-mcp

Минималистичный Model Context Protocol (MCP) сервер, написанный на TypeScript. Разработан для сборки из исходного кода, контейнеризации с помощью Docker и развертывания в IBM Code Engine.


Содержание


Related MCP server: My Awesome MCP

Обзор

Этот сервер поддерживает два транспорта:

Транспорт

Когда используется

Как активировать

stdio

Локальная разработка / Bob desktop

По умолчанию (переменная окружения не нужна)

HTTP Streamable

Docker / Code Engine

MCP_TRANSPORT=http

HTTP-транспорт предоставляет конечную точку /health по адресу GET /health для проверок жизнеспособности (liveness probes).


Структура проекта

.
├── src/
│   └── index.ts          # Server entry point — add tools here
├── build/                # Compiled output (git-ignored)
├── .github/
│   └── workflows/
│       └── build-push.yml  # CI: typecheck → build → push to GHCR
├── Dockerfile            # Multi-stage build (builder + runtime)
├── docker-compose.yml    # Local container testing
├── tsconfig.json
└── package.json

Инструменты

Инструмент

Описание

ping

Проверка работоспособности — возвращает pong и повторяет необязательное сообщение

get_server_info

Возвращает имя сервера, версию, транспорт, версию Node.js и время работы (uptime)


Локальная разработка

Предварительные требования

  • Node.js 20+

  • npm 10+

Установка и сборка

npm install
npm run build

Запуск в режиме stdio (для использования с Bob desktop)

node build/index.js

Локальный запуск в режиме HTTP

MCP_TRANSPORT=http PORT=3000 node build/index.js

Проверьте health-эндпоинт:

curl http://localhost:3000/health

Запуск в Docker

Сборка образа

docker build -t erm-github-mcp .

Запуск контейнера

docker run -p 3000:3000 erm-github-mcp

Использование Docker Compose

docker compose up --build

GitHub Actions CI/CD

The workflow по адресу .github/workflows/build-push.yml запускается при каждом push в ветку main и по тегам версий (v*):

  1. Сборка TypeScript — npm ci + tsc (быстро останавливается при ошибках типов)

  2. Docker build & push — мультиплатформенный образ (linux/amd64, linux/arm64) публикуется в GitHub Container Registry (GHCR)

Образ публикуется как:

ghcr.io/<your-github-username>/erm-github-mcp:<tag>

Настраивать секреты не нужно — рабочий процесс использует встроенный GITHUB_TOKEN.

Как сделать пакет публичным

После первого push перейдите в GitHub → Пакеты → erm-github-mcp → Настройки пакета и установите видимость Public, чтобы Code Engine мог получать образ без учетных данных.


Развертывание в IBM Code Engine

Предварительные требования

  • IBM Cloud CLI with the Code Engine plugin:

    ibmcloud plugin install code-engine
  • Учетная запись IBM Cloud и проект Code Engine

Шаги

1 — Укажите свой проект

ibmcloud ce project select --name <your-project-name>

2 — Разверните приложение

Замените <tag> на тег образа, который необходимо развернуть (например, main или v0.1.0):

ibmcloud ce application create \
  --name erm-github-mcp \
  --image ghcr.io/<your-github-username>/erm-github-mcp:<tag> \
  --port 3000 \
  --min-scale 0 \
  --max-scale 5 \
  --env MCP_TRANSPORT=http \
  --env PORT=3000

3 — Получите публичный URL

ibmcloud ce application get --name erm-github-mcp --output url

4 — Обновите после публикации нового образа

ibmcloud ce application update \
  --name erm-github-mcp \
  --image ghcr.io/<your-github-username>/erm-github-mcp:<new-tag>

Переменные окружения

Переменная

По умолчанию

Описание

MCP_TRANSPORT

stdio

В контейнерах установите http

PORT

3000

HTTP-порт, который слушает сервер


Подключение к Bob (IBM Bob Desktop)

HTTP (удалённо — после развертывания в Code Engine)

Добавьте в файл mcp.json в Bob следующее:

{
  "mcpServers": {
    "erm-github-mcp": {
      "url": "https://<your-code-engine-url>"
    }
  }
}

stdio (локально — для разработки)

{
  "mcpServers": {
    "erm-github-mcp": {
      "command": "node",
      "args": ["/absolute/path/to/erm-github-mcp/build/index.js"]
    }
  }
}

Расширение сервера

Добавляйте новые инструменты в файл src/index.ts через server.tool():

server.tool(
  "my_tool",
  "Description shown to the AI",
  {
    input_field: z.string().describe("What this field does"),
  },
  async ({ input_field }) => ({
    content: [{ type: "text", text: `Result: ${input_field}` }],
  })
);

Затем пересоберите:

npm run build

Лицензия

Apache 2.0

Available Tools

2 tools
get_server_infoA

Returns metadata about this running MCP server instance.

NameRequiredDescriptionDefault

No parameters

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. 'Returns metadata' implies a read-only operation, but it does not explicitly say so, nor does it disclose what the response contains or whether there are side effects. For a zero-parameter tool this is adequate, but it misses the chance to confirm non-mutating behavior and response shape.

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?

A single, front-loaded sentence with no wasted words. It states the verb, resource, and scope efficiently. Perfect for a zero-parameter tool.

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

Completeness4/5

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

For a simple read-only metadata tool with no parameters and no output schema, the description is mostly complete. It tells the agent what the tool does. However, it could be slightly more explicit about the types of metadata returned (e.g., server version, protocol, capabilities) and could mention that it is safe to call without side effects. The lack of any relationship to 'ping' also leaves a small gap.

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

Parameters4/5

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

The tool has zero parameters, so there is nothing for the description to explain beyond what the schema already shows (empty properties). The baseline is 4 because the schema fully covers parameters, and the description adds no ambiguity. No extra value needed.

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 states a clear verb ('Returns') and resource ('metadata about this running MCP server instance'). It distinguishes from ping (which implies liveness check), though 'metadata' is generic and could be more specific about what metadata (e.g., version, capabilities). Still, the purpose is unmistakable.

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?

No guidance on when to use this vs the sibling tool 'ping'. Both relate to server status, but the description doesn't explain which to call for what. An agent would have to infer that ping checks connectivity while this fetches metadata, but no explicit when/when-not is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

pingA

Health-check tool. Returns 'pong' and echoes the optional message back.

NameRequiredDescriptionDefault
messageNoOptional message to echo back

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it discloses both the return value ('pong') and the side effect (echoing the message). 'Health-check' strongly implies a non-mutating, safe operation. It does not explicitly state non-destructiveness, but for a ping the disclosed behavior is effectively complete.

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?

Two short sentences, no filler, with the purpose front-loaded before the return-behavior detail. Every word earns its place; this is a model of concise health-check documentation.

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

Completeness5/5

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

For a tool this simple — one optional parameter, no required fields, no nested objects, no output schema — the description tells an agent everything needed to call it correctly and predict the response. Nothing meaningful is missing.

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?

Schema coverage is 100%, so the single message parameter is already documented ('Optional message to echo back'). The description reinforces the echo behavior in prose, which adds marginal context beyond the schema but does not materially expand on it, landing at the baseline for high-coverage schemas.

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

Purpose5/5

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

The description states a specific purpose ('health-check tool') and the precise behavior ('returns pong and echoes the optional message back'). This is clear, specific, and inherently distinguishes it from the get_server_info sibling, whose name implies returning server details rather than a liveness signal.

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

Usage Guidelines3/5

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

The 'health-check tool' phrasing implies when it should be used, and it is self-evident for a ping utility. However, there is no explicit guidance on when to prefer this over get_server_info or any stated exclusions. For a trivial tool the context is clear enough, but it stops short of explicit alternative routing.

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. 2 tool updatesv0.1.0
    • First observedget_server_info
    • First observedping

TDQS

A3.5/5.0

Scored across 2 tools

Disambiguation5/5

The two tools serve clearly distinct purposes: ping is a health check, while get_server_info provides instance metadata. There is zero overlap between them.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern (ping, get_server_info) with snake_case, matching the expected convention.

Tool Count1/5

With only two generic tools and a server name indicating GitHub integration, the count is severely inadequate. The tools are trivial and unrelated to the apparent domain, representing an extreme mismatch.

Completeness1/5

The server name implies GitHub functionality, but the tool surface offers only health check and server info. No GitHub operations exist, leaving obvious and critical gaps.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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