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Google Play Console MCP

Google Play Console MCP

by abd3lraouf-studios
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Update Testers

update_testers

Assign Google Groups to a testing track (internal, alpha, beta) in Google Play Console, replacing current testers for that track.

Instructions

Update testers for a specific testing track.

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": {
      "package_name": "<package_name>",
      "track": "<track>",
      "google_groups": "<google_groups>"
    },
    "name": "update_testers"
  }
}

Input Schema

NameRequiredDescriptionDefault
trackYesTrack name (internal, alpha, beta)
package_nameYesApp package name
google_groupsYesList of Google Group email addresses

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates mutation ('Update') but does not clarify whether google_groups replaces the full tester list or merges with existing testers, nor does it mention preconditions or side effects. This ambiguity is significant for a write operation.

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?

The description is a single, efficient sentence with the action and resource front-loaded. There is no filler, though the conciseness comes at the expense of behavioral detail.

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 simple three-parameter tool with full schema coverage and an output schema, the required inputs are adequately represented. However, the missing semantics around replacement versus append of testers and lack of usage guidance leave a clear gap in the agent's ability to invoke it with full confidence.

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 description coverage is 100%, with each parameter clearly described in the schema, so the baseline is 3. The description adds only marginal context by tying the operation to a 'specific testing track' and does not meaningfully enhance understanding of the parameters.

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 uses a specific verb ('Update') and resource ('testers for a specific testing track'), clearly indicating what the tool does. However, it does not distinguish itself from related sibling tools such as get_testers or update_track, so it is not maximally differentiated.

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?

There is no guidance about when to use this tool versus alternatives, such as using get_testers to read the current tester list or update_track for broader track configuration. The description states the operation but gives no context for selection.

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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