Google Play MCP

reporting_list_anomalies

List anomalies in an app's vitals to spot sudden crash or ANR-rate changes using Google Play Reporting API data.

Instructions

List anomalies Google detected in an app's vitals (sudden crash/ANR-rate changes). OPTIONAL Reporting API. Read-only.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "packageName": "<packageName>"
    },
    "name": "reporting_list_anomalies"
  }
}

Input Schema

Name	Required	Description	Default
`filter`	No	e.g. activeBetween("2026-01-01T00:00:00Z", UNBOUNDED)
`packageName`	Yes	Application id (package name), e.g. com.example.app

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 10, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description does supply two behavioral facts on its own: the operation is "Read-only" and it depends on an optional API being enabled. It stops short of disclosing anything about anomaly detection latency, result volume, or pagination, which matter for a list endpoint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact fragments with the core purpose front-loaded and no filler. The telegraphic "OPTIONAL Reporting API" phrasing is slightly abrupt but still parses cleanly.

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

Completeness3/5

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

For a two-parameter read-only list tool with full schema coverage and no output schema, the essentials are present. The gap is that nothing describes what an anomaly record contains or how the filter scope affects results, leaving the agent to discover the return shape by calling it.

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% and both parameters are documented in-schema, including a filter example, so the schema carries the load. The description adds no per-parameter meaning beyond what is already structured, making the baseline 3 appropriate.

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 names a specific verb and resource ("List anomalies Google detected in an app's vitals") and clarifies what counts as an anomaly with the parenthetical "sudden crash/ANR-rate changes". It does not explicitly contrast itself with the metric-set siblings, but the domain object is distinct enough to route on.

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?

"OPTIONAL Reporting API" signals an opt-in prerequisite, which is useful context for deciding whether the call will work. However, it never states when to reach for this versus reporting_get_metric_set or reporting_query_metric_set, nor what to do if the API is not enabled.

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

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