GCP Platform Engineer

Name: GCP Platform Engineer
Author: deBilla

作者：deBilla版本 0.4.0i★ –i在你的电脑上运行

注册名称io.github.deBilla/platform-mcp

安装

概览

作者提供的说明（英文原文）

Read-only GCP tools for debugging incidents and finding cost savings

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 开发者工具

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
需要你自己填写： PLATFORM_MCP_ENVIRONMENTS, PLATFORM_MCP_DEFAULT_ENVIRONMENT, PLATFORM_MCP_CONFIG, PLATFORM_MCP_AUDIT_LOG

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "platform": {
      "command": "uvx",
      "args": [
        "platform-mcp"
      ],
      "env": {
        "PLATFORM_MCP_ENVIRONMENTS": "your-value",
        "PLATFORM_MCP_DEFAULT_ENVIRONMENT": "your-value",
        "PLATFORM_MCP_CONFIG": "your-value",
        "PLATFORM_MCP_AUDIT_LOG": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add platform --env PLATFORM_MCP_ENVIRONMENTS=your-value --env PLATFORM_MCP_DEFAULT_ENVIRONMENT=your-value --env PLATFORM_MCP_CONFIG=your-value --env PLATFORM_MCP_AUDIT_LOG=your-value -- uvx platform-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "platform": {
      "command": "uvx",
      "args": [
        "platform-mcp"
      ],
      "env": {
        "PLATFORM_MCP_ENVIRONMENTS": "your-value",
        "PLATFORM_MCP_DEFAULT_ENVIRONMENT": "your-value",
        "PLATFORM_MCP_CONFIG": "your-value",
        "PLATFORM_MCP_AUDIT_LOG": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "platform": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "platform-mcp"
      ],
      "env": {
        "PLATFORM_MCP_ENVIRONMENTS": "your-value",
        "PLATFORM_MCP_DEFAULT_ENVIRONMENT": "your-value",
        "PLATFORM_MCP_CONFIG": "your-value",
        "PLATFORM_MCP_AUDIT_LOG": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

PLATFORM_MCP_ENVIRONMENTS env
JSON map of environment name to GCP settings. Omit when using a config file at ~/.config/platform-mcp/config.toml.
PLATFORM_MCP_DEFAULT_ENVIRONMENT env
Environment used when a tool call omits the environment argument.
PLATFORM_MCP_CONFIG env
Path to a TOML config file, overriding ~/.config/platform-mcp/config.toml.
PLATFORM_MCP_AUDIT_LOG env
Path for the JSONL tool-call audit log, or 'off' to disable it.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 deBilla 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

星标数多于此分类中其他 1391 个服务器的 0%
发布到注册中心的时间比此分类中其他 1391 个服务器的 47% 更新
基础检查结果等于或优于此分类中其他 1391 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

GCP Platform Engineer 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.4.0）于2个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

作者：github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT3天前更新

安装

Desktop Commander

作者：wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT15天前更新

安装

Cloudflare MCP

作者：cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

platform-mcp

mcp-name: io.github.deBilla/platform-mcp

A read-only Model Context Protocol server that turns an AI agent (Claude Code, Claude Desktop, or any MCP client) into a GCP platform engineer. Point it at your Google Cloud projects and ask it to investigate incidents, take inventory, and surface cost-optimization opportunities — all without any ability to change your infrastructure.

Observation only. No tool in this server mutates state. Combined with a viewer-only identity (below), that gives you a hard, defense-in-depth guarantee that an agent can look but never touch.

What it can do

Area	Tools
Environments	`list_environments`
Logs & errors	`query_logs`, `get_recent_errors`, `list_error_groups`
Metrics & alerting	`query_metric`, `list_alert_policies`, `list_uptime_checks`
Cost & recommendations	`get_cost_breakdown`, `get_billing_info`, `list_cost_recommendations`, `list_recommendations`
Resource inventory	`search_assets`, `list_compute_instances`, `list_cloud_run_services`, `list_gke_clusters`, `list_sql_instances`

Typical prompts once it's connected:

*"What are the top error groups in the last 24 hours, and which one is newest?"*
*"Which GKE node pools are over-provisioned? Show mean CPU against machine type."*
*"Where can I reduce spend in this project?"*

Multiple environments

One server can reach several projects. Define them under PLATFORM_MCP_ENVIRONMENTS (see Configuration) and the agent picks one from the wording of your prompt:

*"Any errors in staging in the last hour?"*
*"Compare Cloud Run services between staging and prod."*

Every tool takes an optional environment argument. Omit it and the default environment is used; pass environment="production" to target another. Names, any aliases you define, common shorthands (prod, stg, qa, …) and bare project ids all resolve. An unrecognized name is an error listing the valid options — a typo can never silently retarget the wrong project.

Each environment carries its own service account, so staging and production are reached through separate identities from the same process, and every result echoes back the environment and project it came from.

Requirements

Python 3.11+
A Google Cloud project and credentials (your own login, or a service account)
The gcloud CLI for the one-time setup

Install

uvx platform-mcp          # no install step; uv fetches it on demand

pipx install platform-mcp # or keep it on PATH

From a checkout, for development:

git clone https://github.com/deBilla/platform-mcp.git

cd platform-mcp python3 -m venv .venv ./.venv/bin/pip install -e ".[dev]"

Check your setup

platform-mcp doctor

This checks, for every configured environment, that Application Default Credentials exist, that the read-only service account can be impersonated, that a real API read succeeds, and that the billing export is readable — printing the exact command to fix whatever fails. Run it before reporting a problem.

One-time GCP setup

Run these once per project you want to reach — staging and production each need their own APIs enabled and their own read-only service account.

1. Enable the APIs the tools depend on:

gcloud services enable \

logging.googleapis.com monitoring.googleapis.com clouderrorreporting.googleapis.com \ recommender.googleapis.com cloudasset.googleapis.com cloudbilling.googleapis.com \ bigquery.googleapis.com \ --project YOUR_PROJECT_ID

2. Grant read-only access to the identity the server runs as.

For local development with your own login (Application Default Credentials):

gcloud auth application-default login

The identity needs these viewer roles on the project, plus roles/billing.viewer on the billing account:

roles/viewer                # broad read (compute, run, gke, sql via Asset Inventory)

roles/logging.viewer roles/monitoring.viewer roles/errorreporting.viewer roles/recommender.viewer roles/cloudasset.viewer roles/bigquery.dataViewer # only for get_cost_breakdown roles/bigquery.jobUser # only for get_cost_breakdown

3. (Recommended) Use a dedicated read-only service account instead of your login. platform-mcp setup does every step below, is safe to re-run, and prints the config stanza at the end. It ships with the package, so there is nothing to clone:

uvx platform-mcp setup \

--project YOUR_PROJECT_ID \ --user you@example.com \ --billing-dataset YOUR_BILLING_PROJECT:billing # optional

Or by hand:

PROJECT=YOUR_PROJECT_ID

gcloud iam service-accounts create platform-mcp-ro \ --display-name "platform-mcp read-only" --project $PROJECT

SA=platform-mcp-ro@$PROJECT.iam.gserviceaccount.com for ROLE in roles/viewer roles/logging.viewer roles/monitoring.viewer \ roles/errorreporting.viewer roles/recommender.viewer roles/cloudasset.viewer \ roles/bigquery.jobUser; do gcloud projects add-iam-policy-binding $PROJECT \ --member="serviceAccount:$SA" --role="$ROLE" --condition=None done

Let your own login impersonate it (no key file to manage):

gcloud iam service-accounts add-iam-policy-binding $SA \ --member="user:you@example.com" \ --role="roles/iam.serviceAccountTokenCreator" --project $PROJECT

The grant everyone forgets. roles/bigquery.jobUser above only lets the account *start* a query; it grants no access to any data. A billing export almost always lives in a different project, so the account also needs read on that dataset. Without it get_cost_breakdown returns 403 while every other tool works, which reads like a bug in the tool rather than a missing grant:

bq add-iam-policy-binding \

--member="serviceAccount:$SA" --role=roles/bigquery.dataViewer \ YOUR_BILLING_PROJECT:billing

If you lack admin on the billing project, that one line is what to send to someone who has it. platform-mcp doctor checks it and says which side is missing.

Then reference it as that environment's impersonate value in PLATFORM_MCP_ENVIRONMENTS (preferred — no key file), or point at a downloaded key via GOOGLE_APPLICATION_CREDENTIALS.

Impersonation is performed by whatever identity your ADC resolves to. If your

ADC is itself an impersonated service account, that SA — not your user — needs

roles/iam.serviceAccountTokenCreator on each platform-mcp-ro.

Security model

Read-only is enforced by IAM, not by OAuth scope. The server requests the broad cloud-platform scope and stays read-only purely because it never calls a mutating API. Do not rely on the code alone — run it under a viewer-only identity (step 3 above) so the credential itself is incapable of writing, regardless of what code executes. This gives you two independent layers: the server doesn't try to write, and the identity couldn't if it did.

With multiple environments this stays per-project: each environment authenticates as its own service account, so a staging identity is never used to reach production. Grant each one viewer-only access to its project alone.

Configuration

The friendliest option is a config file, which keeps project ids and service account emails out of every client config you own:

mkdir -p ~/.config/platform-mcp

cp config.toml.example ~/.config/platform-mcp/config.toml $EDITOR ~/.config/platform-mcp/config.toml

With that in place, registering the server takes no environment variables at all. Point PLATFORM_MCP_CONFIG elsewhere to use a different file — a copy committed to your infrastructure repo, for instance.

Environment variables still work and always win over the file, so an existing setup keeps running unchanged and a one-off override needs no edit:

Variable	Purpose
`PLATFORM_MCP_ENVIRONMENTS`	JSON map of environment name → settings. The recommended way to configure the server.
`PLATFORM_MCP_DEFAULT_ENVIRONMENT`	Environment used when a tool call omits `environment`. Defaults to `staging` if configured, else the first entry.
`GOOGLE_APPLICATION_CREDENTIALS`	Path to a read-only SA key file (alternative to impersonation).

PLATFORM_MCP_ENVIRONMENTS holds a JSON object; each entry accepts:

Key	Purpose
`project`	Required. GCP project id.
`impersonate`	Read-only SA to impersonate for this environment (no key file needed).
`billing_export_table`	Fully-qualified BigQuery billing export table, required only for `get_cost_breakdown` (e.g. `YOUR_PROJECT_ID.billing.gcp_billing_export_v1_XXXXXX`).
`aliases`	Extra names the agent may use for this environment.

A bare string value is shorthand for {"project": "..."}. As JSON inside .mcp.json the quotes must be escaped; unescaped it reads:

"staging": { "project": "my-app-staging", "impersonate": "platform-mcp-ro@my-app-staging.iam.gserviceaccount.com" }, "production": { "project": "my-app", "impersonate": "platform-mcp-ro@my-app.iam.gserviceaccount.com", "billing_export_table": "my-app.billing.gcp_billing_export_v1_XXXXXX" } }

Single-environment mode. If PLATFORM_MCP_ENVIRONMENTS is unset the server behaves as before, exposing one environment named default:

Variable	Purpose
`GCP_PROJECT`	Target project. Falls back to your ADC default project if unset.
`IMPERSONATE_SERVICE_ACCOUNT`	Read-only SA to impersonate. Also the fallback for registry entries with no `impersonate`.
`BILLING_EXPORT_TABLE`	Billing export table. Also the fallback for registry entries with no `billing_export_table`.

Register with a client

Claude Code — with a config file in place, this is the whole thing:

claude mcp add platform-mcp --scope user -- uvx platform-mcp

Claude Desktop — needs an absolute path to uvx; see Claude Desktop for the full walkthrough.

Without a config file, add the environment variables from .mcp.json.example to either form.

Skip the approval prompt

Every tool here is read-only, so approving each call individually adds nothing. Allow the whole server once, in Claude Code settings:

{ "permissions": { "allow": ["mcp__platform-mcp__*"] } }

The glob must sit after a literal mcp__ __ prefix — an unanchored pattern like mcp__* is ignored with a warning and approves nothing.

MCP Inspector — for interactive testing:

uvx --with 'mcp[cli]' mcp dev src/platform_mcp/server.py

Claude Desktop

Installing for a teammate who uses Claude Desktop rather than the CLI. It works the same as Claude Code, with one failure mode the CLI does not have.

Claude Desktop does not inherit your shell `PATH`. It launches from the Finder, so uvx and anything installed by Homebrew or uv are invisible to it. A config that says "command": "uvx" fails with ENOENT — the server never starts, and the error names the command rather than the reason. The command path must be absolute.

What does *not* break is credentials. Application Default Credentials are a file the Google libraries read directly, so gcloud is needed once, in a terminal, to create that file — not at runtime. The config file is found the same way, from the home directory, whatever launched the server.

Before you start: the admin grant

Each person impersonates the read-only service accounts, so an admin runs this once per person, per environment (the platform-mcp setup script does it for whoever runs it, but not for anyone else):

gcloud iam service-accounts add-iam-policy-binding \

platform-mcp-ro@YOUR_PROJECT_ID.iam.gserviceaccount.com \ --member="user:teammate@example.com" \ --role="roles/iam.ser

只显示了开头部分；其余内容请在仓库中阅读