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Payware MCP Server

Payware MCP Server

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payware_products_get_next_airings

Read-onlyIdempotent

Retrieve a product placement's next airings in each rule's time zone to verify scheduling behavior, including daylight-saving shifts, before relying on the rule.

Instructions

[Merchant] A placement's next airings, each in its rule's time zone so daylight-saving shifts are visible. Use it to check a rule does what was meant before relying on it.

Endpoint: GET /products/{productId}/placements/{placementId}/airings/next

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": {
      "productId": "<productId>",
      "placementId": "<placementId>"
    },
    "name": "payware_products_get_next_airings"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoHow many, 1 to 100. Default 10
productIdYesThe product's ID: pr + 8 letters or digits, e.g. pr7e4rCToG
useSandboxNoUse the sandbox (the default) rather than production
placementIdYesThe placement's ID: pl + 8 letters or digits, e.g. pl7e4rCToG

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.2.0

TDQS

A3.8/5.0
Behavior3/5

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

The annotations already establish that this is a safe, read-only, idempotent, open-world operation, so the safety profile is covered. The description adds useful behavioral context about time zones and daylight-saving visibility, but it does not explain return shape, ordering, or pagination behavior beyond the count parameter.

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 short and front-loaded, leading with what the tool returns and then giving the operational purpose. The endpoint line is compact and no sentence is redundant.

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

Completeness4/5

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

For a four-parameter read-only tool with full schema coverage and annotations, the description is largely complete, especially in explaining the time-zone behavior of returned airings. It could be stronger by clarifying how results differ from the sibling airing-list tools, but no critical calling information is missing.

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%, so productId, placementId, count, and useSandbox are already well documented in the input schema. The description adds no parameter-specific meaning beyond the schema, so baseline 3 applies.

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 states the resource and action: retrieving a placement's next airings. It is specific enough to distinguish from generic placement/product getters, though it does not explicitly differentiate itself from sibling tools like payware_products_list_airings or payware_products_get_airing_calendar.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear use case: verifying that a rule behaves as intended before relying on it. That is a concrete when-to-use signal, but it offers no when-not-to-use guidance or named alternatives such as the list or calendar variants.

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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