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Genesys Cloud MCP Server

Genesys Cloud MCP Server

by Roshan1491
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TypeScript
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oauth_client_usage

Retrieves OAuth client usage for a specified period, returning total requests and a breakdown of Platform API endpoints called.

Instructions

Retrieves the usage of an OAuth Client for a given period. It returns the total number of requests and a breakdown of Platform API endpoints used by the client.

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": {
      "oauthClientId": "<oauthClientId>",
      "startDate": "<startDate>",
      "endDate": "<endDate>"
    },
    "name": "oauth_client_usage"
  }
}

Input Schema

NameRequiredDescriptionDefault
endDateYesThe end date/time in ISO-8601 format (e.g., '2024-01-07T23:59:59Z')
startDateYesThe start date/time in ISO-8601 format (e.g., '2024-01-01T00:00:00Z')
oauthClientIdYesThe UUID of the OAuth Client to retrieve the usage for (e.g., 00000000-0000-0000-0000-000000000000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A3.8/5.0
Behavior4/5

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

There are no read-only/destructive annotations, but the description clearly indicates a read operation ('Retrieves') and discloses the concrete output: total request count and per-endpoint breakdown. This goes beyond the schema by explaining what the operation returns, though it does not discuss auth requirements or edge cases like empty results.

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?

Two short sentences with no filler. The purpose is front-loaded and the return behavior is stated immediately, making it easy for an agent to parse quickly.

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 simple read-only tool with three fully documented parameters and no output schema, the description adequately covers what the tool does and what it returns. It could add a bit more about response structure or usage conditions, but nothing critical is missing for correct invocation.

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 the parameters are fully documented in the input schema. The description only rephrases the time-period concept and does not add new parameter-level semantics beyond what the schema already provides.

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 ('Retrieves') and a clear resource ('usage of an OAuth Client for a given period'), and it specifies what is returned: total requests and endpoint breakdown. It is clearly distinct from the sibling tool 'oauth_clients' (which likely manages clients), though it does not explicitly name or differentiate itself from that sibling.

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?

The description implies when to use the tool (when OAuth client usage data is needed), but it does not provide explicit when-to-use/when-not-to-use guidance or mention alternatives. The agent must infer usage context from the function description and sibling list.

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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