google-play-developer-mcp

purchases_subscriptions_v2_revoke

Revoke a subscription to automatically refund the user and terminate their access. Optionally apply per-item refunds for granular control.

Instructions

Revoke a subscription (refund + terminate access). 2025-05 added itemBasedRefund option for per-item refunds.

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>",
      "token": "<token>"
    },
    "name": "purchases_subscriptions_v2_revoke"
  }
}

Input Schema

Name	Required	Description
`token`	Yes	Purchase token returned by the Play Billing library
`packageName`	Yes	Android application package name, e.g. com.example.app
`revocationContext`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.2Jun 2, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It indicates the action is mutative (refund + terminate), but does not disclose reversibility, permission requirements, rate limits, or side effects on the purchase token. The mention of 'itemBasedRefund' adds minimal context.

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

Conciseness5/5

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

The description is very concise: two sentences that efficiently convey the core action and a notable new feature. No redundant information, and the key details are front-loaded.

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

Completeness2/5

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

Given the tool has a nested object parameter, no output schema, and no annotations, the description should provide more context. It does not explain the revocationContext object's fields (beyond implying 'itemBasedRefund'), expected return values, or prerequisites. This leaves significant gaps for an AI agent.

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?

With 67% schema coverage, the baseline is 3. The description adds value by referencing the 'itemBasedRefund' option, which likely relates to the 'revocationContext' parameter, but does not explicitly connect it or explain its structure. More detail on the nested object would improve this score.

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 clearly defines the verb 'revoke' and the resource 'subscription', and elaborates that it includes both refund and termination of access. This distinguishes it from sibling tools like cancel or defer. However, it does not explicitly contrast with these siblings, leaving some ambiguity for an AI agent.

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?

The description lacks explicit guidance on when to use this tool versus the many sibling subscription tools (e.g., cancel, defer). It only mentions a new 'itemBasedRefund' option added in 2025-05, which hints at a specific use case but does not provide comprehensive usage context.

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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