# GCP Platform Engineer (pypi · platform-mcp)

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

- Trust score: 59/100 (low)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- pypi · `platform-mcp`: 59/100 (this document), [markdown](https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp.md), [page](https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp)

## Channel facts

- Registry: `pypi`
- Package: `platform-mcp`
- Version: `0.4.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Supply Chain Security**: 50/100
  - Malware scan not yet available for this package.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs setuptools.build_meta at install time, a recognised native-build step with no shell scripting around it.
  - 1 of 63 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 32/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - License check failed: no license is declared.
  - Actively maintained (last published 18 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 70/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 2337 tokens (~146/item across 16 items; 16 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 70/100
  - Stability observed for 21 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 67/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 0% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 16 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 17 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the GCP Platform Engineer MCP server?

GCP Platform Engineer runs locally as a PyPI package, launched with uvx platform-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add debilla-platform-mcp -- uvx platform-mcp
```

### Cursor

```json
{
  "mcpServers": {
    "debilla-platform-mcp": {
      "command": "uvx",
      "args": [
        "platform-mcp"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "debilla-platform-mcp": {
      "command": "uvx",
      "args": [
        "platform-mcp"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add debilla-platform-mcp -- uvx platform-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "debilla-platform-mcp": {
      "type": "local",
      "command": [
        "uvx",
        "platform-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add debilla-platform-mcp --command uvx --arg platform-mcp
```

### Hermes

```yaml
mcp_servers:
  debilla-platform-mcp:
    command: "uvx"
    args: ["platform-mcp"]
```

### Netclaw

```json
{
  "McpServers": {
    "debilla-platform-mcp": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "platform-mcp"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add debilla-platform-mcp -t stdio -c uvx -a platform-mcp
```

### Other

```json
{
  "mcpServers": {
    "debilla-platform-mcp": {
      "command": "uvx",
      "args": [
        "platform-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-19 (score 59, +1)

No change was recorded against any check on this day. Stability & Change Management went from 63 to 67. That category is still filling its 30-day observation window: 19 days of observed history at the previous scan, 20 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-17 (score 58, +1)

No change was recorded against any check on this day. Stability & Change Management went from 57 to 60. That category is still filling its 30-day observation window: 17 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-15 (score 57, +1)

- [functional regression] Security disclosure: unverified → fail

### 2026-09-14 (score 56, 0)

- [functional regression] Security disclosure: fail → unverified

### 2026-09-13 (score 56, +1)

No change was recorded against any check on this day. Stability & Change Management went from 43 to 47. That category is still filling its 30-day observation window: 13 days of observed history at the previous scan, 14 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-10 (score 55, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-08 (score 54, −14)

- [security regression] Malware scan: pass → unverified

### 2026-09-06 (score 68, +16)

- [security improvement] Malware scan: unverified → pass

## MCP tools (16)

### `list_environments` (~90 tokens)

List the GCP environments this server can query and which is the default.

Pass one of the returned names as the `environment` argument of any other
tool to target that project (e.g. environment='production'). Omitting the
argument uses the default environment shown here. Common shorthands such as
'prod' and 'stg' are accepted, as is a bare project id.

### `query_logs` (~166 tokens)

Query Cloud Logging with an advanced-filter expression.

Args:
    filter: Cloud Logging advanced filter (e.g. 'severity>=WARNING AND
        resource.type="cloud_run_revision"'). Leave empty to match all logs.
    freshness: How far back to look, e.g. '30m', '1h', '2d'. Default '1h'.
    limit: Maximum number of entries to return (newest first).
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment. Call
        list_environments to see what is configured.

Input parameters:

- `environment` (string)
- `filter` (string)
- `freshness` (string)
- `limit` (integer)

### `get_recent_errors` (~130 tokens)

Return recent log entries at severity ERROR or higher.

Args:
    service: Optional service name to narrow to (matched against
        resource.labels.service_name and logName).
    hours: How many hours back to search. Default 1.
    limit: Maximum number of entries to return (newest first).
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `hours` (integer)
- `limit` (integer)
- `service` (string)

### `list_error_groups` (~149 tokens)

List grouped application errors from Error Reporting with counts.

Args:
    hours: Lookback window; snapped to the nearest supported period
        (1h, 6h, 1d, 1w, 30d). Default 24.
    service: Optional service name filter (Error Reporting "service" label).
    limit: Maximum number of error groups to return (most frequent first).
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `hours` (integer)
- `limit` (integer)
- `service` (string)

### `query_metric` (~243 tokens)

Query a Cloud Monitoring metric time series.

Args:
    metric_type: Metric type, e.g. 'compute.googleapis.com/instance/cpu/utilization'.
    resource_filter: Optional extra filter, e.g. 'resource.labels.instance_id="123"'.
    window: How far back to query, e.g. '1h', '6h', '1d'. Default '1h'.
    aligner: Aggregation across the alignment period: MEAN, MAX, MIN, SUM,
        COUNT, RATE, PERCENTILE_99. Default MEAN.
    alignment_period: Bucket size for aggregation, e.g. '1m', '5m'. Default '5m'.
    limit: Maximum number of time series to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `aligner` (string)
- `alignment_period` (string)
- `environment` (string)
- `limit` (integer)
- `metric_type` (string, required)
- `resource_filter` (string)
- `window` (string)

### `list_alert_policies` (~78 tokens)

List Cloud Monitoring alert policies and whether they are enabled.

Args:
    limit: Maximum number of policies to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

### `list_uptime_checks` (~75 tokens)

List Cloud Monitoring uptime check configurations.

Args:
    limit: Maximum number of uptime checks to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

### `list_cost_recommendations` (~170 tokens)

Aggregate GCP cost-optimization recommendations (idle/rightsizing/etc).

Fans out the cost recommenders across the locations where the project has
resources. Recommenders/locations that are empty or not enabled are skipped.

Args:
    locations: Optional comma-separated zones/regions to scan (e.g.
        'us-central1,us-central1-a'). If empty, auto-discovers from Asset
        Inventory (requires the Cloud Asset API).
    limit_per_call: Max recommendations to pull per recommender+location.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit_per_call` (integer)
- `locations` (string)

### `list_recommendations` (~172 tokens)

List recommendations from a specific recommender at a specific location.

Args:
    recommender_id: Recommender id, e.g.
        'google.compute.instance.MachineTypeRecommender' or
        'google.iam.policy.Recommender'.
    location: Zone (e.g. 'us-central1-a'), region (e.g. 'us-central1'), or
        'global' depending on the recommender. Default 'global'.
    limit: Maximum number of recommendations to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)
- `location` (string)
- `recommender_id` (string, required)

### `get_cost_breakdown` (~289 tokens)

Summarize recent spend from the BigQuery billing export.

By default this reports spend for the selected environment's project only.
A billing export table covers every project on the billing account, and
several environments commonly share one table, so an unfiltered query would
return identical account-wide totals for staging and production.

Only the environment holding the export needs 'billing_export_table' set:
one billing account exports to one project, and that export already covers
every project on the account. Asking any other environment for costs returns
an error naming the one that has it.

Args:
    group_by: One of 'service', 'sku', 'project', 'region'. Default 'service'.
    days: Lookback window in days over usage_start_time. Default 30.
    limit: Max rows returned (highest net cost first).
    all_projects: Report the whole billing account instead of just this
        environment's project. Pair with group_by='project' to compare
        projects; the totals then are not specific to this environment.
    environment: Which configured GCP environment to bill against, e.g.
        'staging' or 'production'. Omit to use the default environment.

Input parameters:

- `all_projects` (boolean)
- `days` (integer)
- `environment` (string)
- `group_by` (string)
- `limit` (integer)

### `get_billing_info` (~62 tokens)

Return the billing account linked to the project and its status.

Args:
    environment: Which configured GCP environment to inspect, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)

### `search_assets` (~229 tokens)

Search all cloud resources in the project via Cloud Asset Inventory.

Args:
    asset_types: Optional comma-separated asset types to filter, e.g.
        'compute.googleapis.com/Instance,run.googleapis.com/Service'.
    query: Optional free-text/structured query, e.g. 'state:RUNNING' or
        'location:us-central1'.
    limit: Maximum number of resources to return. Default 50; raise it when
        you know you need a full inventory, since each resource costs
        context.
    include_labels: Include resource labels. Off by default because
        deployment labels are usually the largest part of the response and
        rarely answer the question being asked.
    environment: Which configured GCP environment to search, e.g. 'staging'
        or 'production'. Omit to use the default environment. Call
        list_environments to see what is configured.

Input parameters:

- `asset_types` (string)
- `environment` (string)
- `include_labels` (boolean)
- `limit` (integer)
- `query` (string)

### `list_compute_instances` (~76 tokens)

List Compute Engine VM instances with location and status.

Args:
    limit: Maximum number of instances to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

### `list_cloud_run_services` (~72 tokens)

List Cloud Run services.

Args:
    limit: Maximum number of services to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

### `list_gke_clusters` (~77 tokens)

List GKE (Kubernetes Engine) clusters.

Args:
    limit: Maximum number of clusters to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

### `list_sql_instances` (~71 tokens)

List Cloud SQL instances.

Args:
    limit: Maximum number of instances to return.
    environment: Which configured GCP environment to query, e.g. 'staging'
        or 'production'. Omit to use the default environment.

Input parameters:

- `environment` (string)
- `limit` (integer)

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp#diagnostics

## Score history

- 2026-09-20: 59
- 2026-09-19: 59
- 2026-09-18: 58
- 2026-09-17: 58
- 2026-09-16: 57
- 2026-09-15: 57
- 2026-09-14: 56
- 2026-09-13: 56
- 2026-09-12: 55
- 2026-09-11: 55
- 2026-09-10: 55
- 2026-09-09: 54
- 2026-09-08: 54
- 2026-09-07: 68
- 2026-09-06: 68
- 2026-09-05: 52
- 2026-09-04: 67
- 2026-09-03: 51
- 2026-09-02: 51
- 2026-09-01: 65
- 2026-08-31: 50
- 2026-08-30: 50

## Common questions

### What is the GCP Platform Engineer MCP server?

GCP Platform Engineer is an MCP server listed in the public MCP registry as io.github.deBilla/platform-mcp. Read-only GCP tools for debugging incidents and finding cost savings. This page covers its PyPI package (platform-mcp).

### Is the GCP Platform Engineer MCP server safe to use?

GCP Platform Engineer scores 59 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the GCP Platform Engineer MCP server expose?

GCP Platform Engineer exposes 16 tools: list_environments, query_logs, get_recent_errors, list_error_groups, query_metric, and 11 more. Their descriptions and schemas cost roughly 2,149 tokens of context every time the server is loaded.

### Is the GCP Platform Engineer MCP server still maintained?

GCP Platform Engineer is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- PyPI project: https://pypi.org/project/platform-mcp/
- Socket report: https://socket.dev/pypi/package/platform-mcp
- Repository: https://github.com/deBilla/platform-mcp
- Website: https://debilla.github.io/platform-mcp/
- Changelog RSS feed: https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp.json
- HTML version of this page: https://verifymcp.io/servers/debilla-platform-mcp/platform-mcp