AKS-Lab-GitHubCopilot: Skill for Claude Code

.github/skills/mcp-server-skeleton/SKILL.md

mcp-server-skeleton is a skill for Claude Code, Codex from microsoft/AKS-Lab-GitHubCopilot. It costs 0 tokens per session (554 once invoked), scanned A, original, MIT.

A starting template for building an MCP server with FastMCP and streamable HTTP. MCP, or Model Context Protocol, is a way for an AI agent to call tools that access data or services.

In plain words
What is it for?
Use it to scaffold a server that exposes tools such as stock lookups, define its data models, implement storage access, and provide health and readiness checks.
Why use it?
It gives new servers a consistent layout, typed input and output models, a storage layer, a Dockerfile, and health endpoints for deployment checks.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

This is microsoft/AKS-Lab-GitHubCopilot's own configuration. It tells Claude Code and Codex how to work on AKS-Lab-GitHubCopilot itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AKS-Lab-GitHubCopilot configures →

About the project

ZavaShop on AKS and Azure Container Apps is a hands-on lab for delivering a multi-agent retail supply-chain application from requirements through deployment. It demonstrates a team of six GitHub Copilot custom coding agents working across specifications, application code, MCP servers, tests, infrastructure, and CI. The catalogue entries define the agents, skills, and instructions used in that workflow.

microsoft/AKS-Lab-GitHubCopilot · 10 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to microsoft/AKS-Lab-GitHubCopilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/microsoft/AKS-Lab-GitHubCopilot/main/.github/skills/mcp-server-skeleton/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/microsoft/AKS-Lab-GitHubCopilot

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/aks-lab-githubcopilot/mcp-server-skeleton"><img src="https://agentmods.dev/badge/skills/microsoft/aks-lab-githubcopilot/mcp-server-skeleton.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 554 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00554
Opus 5.5 $0.00000 $0.00222
Sonnet 5.5 $0.00000 $0.00111
Haiku 4.5 $0.00000 $0.00055

Measured 2mo ago against content hash 84843e3296e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mcp-server-skeleton scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

sleep 1 && curl -fsS http://localhost:8080/healthz
.github/skills/mcp-server-skeleton/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: MCP Server Skeleton (FastMCP, streamable-http)

Reference layout

src/mcp_servers/<name>/
├── __init__.py
├── models.py
├── store.py
├── server.py
└── Dockerfile

server.py template

from __future__ import annotations

from mcp.server.fastmcp import FastMCP
import structlog
from starlette.requests import Request
from starlette.responses import JSONResponse

from .models import StockQuery, StockReport
from .store import lookup_stock

log = structlog.get_logger("<name>-mcp")
mcp = FastMCP("<name>-mcp", host="0.0.0.0", port=8080, streamable_http_path="/mcp")


@mcp.custom_route("/healthz", methods=["GET"])
async def healthz(_request: Request) -> JSONResponse:
    """Return process health for container probes."""

    return JSONResponse({"status": "ok"})


@mcp.custom_route("/readyz", methods=["GET"])
async def readyz(_request: Request) -> JSONResponse:
    """Return readiness for ACA ingress probes."""

    return JSONResponse({"status": "ready", "name": "<name>-mcp"})


@mcp.tool()
async def check_stock(query: StockQuery) -> StockReport:
    """Return on-hand stock and reorder point for each requested location.

    Args:
        query: SKU and list of location IDs.
    Returns:
        StockReport with one LocationStock per requested location.
    """
    log.info("tool.check_stock", sku=query.sku, locations=query.locations)
    return await lookup_stock(query)


if __name__ == "__main__":
    mcp.run(transport="streamable-http")

models.py rules

  • Every request / response is a Pydantic v2 model with model_config = ConfigDict(frozen=True).
  • Field names are snake_case; alias to camelCase only if an external API requires it.

store.py rules

  • In-memory dict keyed by primary key. Leave the marker:
    # TODO: replace with Cosmos DB (see specs/storage.md)
    
  • Seed with at least: SKU ZS-1042; locations store-101, store-202, wh-east.

Acceptance

uv run python -m src.mcp_servers.<name>.server &
sleep 1 && curl -fsS http://localhost:8080/healthz
curl -fsS http://localhost:8080/readyz
kill %1

Read the full file on GitHub · 83 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 83 lines · 0 tokens per session scan A 84843e3296e9

Subscribe to this mod's changes

mcp-server-skeleton is a skill published in the GitHub repository microsoft/AKS-Lab-GitHubCopilot (10 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 554 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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