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servicenow-platform-mcp

servicenow-platform-mcp

by Xerrion
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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resolve_choice

Resolve ServiceNow choice labels to their stored values by specifying table, field, and label. Get the full label-value mapping when no label is provided.

Instructions

Resolve a choice label to its underlying value via ChoiceRegistry.

Args: table: ServiceNow table name. field: Field name on that table. label: Choice label to resolve. When empty, returns the full {label: value} mapping for the field.

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": {
      "table": "<table>",
      "field": "<field>"
    },
    "name": "resolve_choice"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldYes
labelNo
tableYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the conditional behavior (returns mapping if label empty) but does not disclose error handling, authentication requirements, or rate limits. The read-only nature is implied but not explicitly stated.

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 concise with only three sentences, front-loading the purpose and listing parameters efficiently. No unnecessary words.

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?

Given the tool's simplicity and the existence of an output schema, the description covers key behaviors. It could mention the output format more explicitly, but overall it is sufficiently complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite schema description coverage being 0%, the description explicitly explains each parameter: 'ServiceNow table name', 'Field name on that table', and the special behavior of the label parameter when empty. This adds significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: resolving a choice label to its underlying value via ChoiceRegistry. It also distinguishes from siblings by specifying a unique function not shared by other tools in the list.

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 usage for resolving choice labels and optionally getting the full mapping when label is empty. However, it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings.

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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