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erm-github-mcp

erm-github

Ein schlichter Model Context Protocol (MCP)-Server, geschrieben in TypeScript. Er ist dafür gedacht, aus dem Quellcode gebaut, mit Docker containerisiert und auf IBM Code Engine bereitgestellt zu werden.


Inhaltsverzeichnis


Related MCP server: My Awesome MCP

Übersicht

Dieser Server unterstützt zwei Transporte:

Transport

Verwendung

Aktivierung

stdio

Lokale Entwicklung / Bob Desktop

Standard (keine Umgebungsvariable erforderlich)

HTTP Streamable

Docker / Code Engine

MCP_TRANSPORT=http

Der HTTP-Transport stellt einen /health-Endpunkt unter GET /health für Liveness-Proben bereit.


Projektstruktur

.
├── 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

Tools

Tool

Beschreibung

ping

Health-Check – gibt pong und eine optionale Nachricht zurück

get_server_info

Gibt Servername, Version, Transport, Node.js-Version und Uptime zurück


Lokale Entwicklung

Voraussetzungen

  • Node.js 20+

  • npm 10+

Installieren und bauen

npm install
npm run build

Im stdio-Modus ausführen (für die Verwendung mit Bob Desktop)

node build/index.js

Lokal im HTTP-Modus ausführen

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

Testen Sie den Health-Endpunkt:

curl http://localhost:3000/health

Mit Docker ausführen

Docker-Image erstellen

docker build -t erm-github-mcp .

Container ausführen

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

Docker Compose verwenden

docker compose up --build

GitHub Actions CI/CD

Der Workflow in .github/workflows/build-push.yml wird bei jedem Push auf main und bei Versions-Tags (v*) ausgeführt:

  1. TypeScript-Build – npm ci + tsc (bricht bei Typfehlern sofort ab)

  2. Docker-Build & -Push – Multi-Plattform-Image (linux/amd64, linux/arm64), gepusht an die GitHub Container Registry (GHCR)

Das Image wird wie folgt veröffentlicht:

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

Es müssen keine Secrets konfiguriert werden – der Workflow verwendet den integrierten GITHUB_TOKEN.

Paket öffentlich machen

Nach dem ersten Push: Navigieren Sie zu GitHub → Pakete → erm-github-mcp → Paketeinstellungen und setzen Sie die Sichtbarkeit auf Public, damit Code Engine das Image ohne Anmeldedaten abrufen kann.


Bereitstellung auf IBM Code Engine

Voraussetzungen

  • IBM Cloud CLI mit dem Code Engine-Plugin:

    ibmcloud plugin install code-engine
  • Ein IBM-Cloud-Konto und ein Code Engine-Projekt

Schritte

1. Wählen Sie Ihr Projekt aus

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

2. Anwendung bereitstellen

Ersetzen Sie <tag> durch das Image-Tag, das Sie bereitstellen möchten (z. B. main oder 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. Öffentliche URL abrufen

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

4. Nach einem neuen Image-Pushaktualisieren

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

Umgebungsvariablen

Variable

Standard

Beschreibung

MCP_TRANSPORT

stdio

In Containern auf http setzen

PORT

3000

HTTP-Port, auf dem der Server lauscht


Verbindung zu Bob herstellen (IBM Bob Desktop)

HTTP (remote – nach der Bereitstellung auf Code Engine)

Fügen Sie Ihrer Bob-mcp.json Folgendes hinzu:

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

stdio (lokal – für die Entwicklung)

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

Erweitern des Servers

Fügen Sie mit server.tool() neue Tools in src/index.ts hinzu:

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}` }],
  })
);

Danach neu bauen:

npm run build

Lizenz

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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