Dataverse MCP Server

get_option_set_values

Retrieve all option values (numeric code and label) from a Dataverse choice column or global option set. Use these values when filtering or writing records.

Instructions

Fetch all option values (integer code + label) for a Dataverse choice column or global option set. Use tableName + attributeName for a local choice/picklist/status/state column. Use optionSetName for a global option set shared across tables. Returns every option with its numeric value and display label — use these values when filtering or writing records.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_option_set_values"
  }
}

Input Schema

Name	Required	Description
`tableName`	No	Logical name of the table, e.g. 'account'. Required when using attributeName.
`attributeName`	No	Logical name of the choice/picklist/status/state column, e.g. 'industrycode' or 'statecode'.
`optionSetName`	No	Name of a global option set, e.g. 'industrycode'. Use instead of tableName + attributeName.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Aug 10, 2026

TDQS

A4.2/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return type (integer code + label) and that it returns every option. However, it does not mention edge cases such as conflicting parameters, empty results, or required permissions, leaving some behavioral ambiguity.

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 sentences, front-loaded with the core purpose, and every sentence adds value. No redundant information or filler.

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 lookup tool with no output schema and three optional params, the description covers purpose, parameter selection, and return value. It is missing guidance on what happens if no params or conflicting params are provided, but this is a minor gap given the tool's simplicity.

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?

Schema coverage is 100%, with all three parameters well described. The description adds semantic value beyond the schema by explaining the local vs. global distinction and reinforcing which parameter combination to use in which scenario.

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 fetches all option values for a Dataverse choice column or global option set. It distinguishes local vs. global usage and is distinct from sibling CRUD/query/metadata tools.

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 explicitly tells when to use tableName+attributeName (local choice/picklist/status/state) vs. optionSetName (global option set), and mentions the values are useful for filtering/writing. It lacks explicit 'don't use' alternatives but gives clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.