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Dataverse MCP Server

by mwhesse

Delete Dataverse Option Set

delete_dataverse_optionset

Remove an option set from Microsoft Dataverse. This permanent deletion requires verifying no columns currently reference the option set before proceeding.

Instructions

Permanently deletes an option set from Dataverse. WARNING: This action cannot be undone and will fail if the option set is being used by any columns. Ensure no columns reference this option set before deletion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the option set to delete

Implementation Reference

  • The handler function that performs the deletion of the specified global option set using DataverseClient.deleteMetadata, including success response and error handling.
    async (params) => {
      try {
        await client.deleteMetadata(`GlobalOptionSetDefinitions(Name='${params.name}')`);
    
        return {
          content: [
            {
              type: "text",
              text: `Successfully deleted option set '${params.name}'.`
            }
          ]
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: `Error deleting option set: ${error instanceof Error ? error.message : 'Unknown error'}`
            }
          ],
          isError: true
        };
      }
    }
  • Zod schema for the tool input, requiring the name of the option set to delete.
    inputSchema: {
      name: z.string().describe("Name of the option set to delete")
    }
  • The server.registerTool call that registers the 'delete_dataverse_optionset' tool with its schema and handler.
      server.registerTool(
        "delete_dataverse_optionset",
        {
          title: "Delete Dataverse Option Set",
          description: "Permanently deletes an option set from Dataverse. WARNING: This action cannot be undone and will fail if the option set is being used by any columns. Ensure no columns reference this option set before deletion.",
          inputSchema: {
            name: z.string().describe("Name of the option set to delete")
          }
        },
        async (params) => {
          try {
            await client.deleteMetadata(`GlobalOptionSetDefinitions(Name='${params.name}')`);
    
            return {
              content: [
                {
                  type: "text",
                  text: `Successfully deleted option set '${params.name}'.`
                }
              ]
            };
          } catch (error) {
            return {
              content: [
                {
                  type: "text",
                  text: `Error deleting option set: ${error instanceof Error ? error.message : 'Unknown error'}`
                }
              ],
              isError: true
            };
          }
        }
      );
    }
  • src/index.ts:162-162 (registration)
    Top-level call to register the option set tools, including deleteOptionSetTool, with the main MCP server.
    deleteOptionSetTool(server, dataverseClient);
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates critical traits: the action is permanent and irreversible ('cannot be undone'), has a failure condition ('will fail if the option set is being used'), and requires prerequisite checks ('Ensure no columns reference this option set'). However, it doesn't mention authentication needs, rate limits, or error handling specifics.

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 front-loaded with the core action and warning, followed by specific usage guidance. Every sentence earns its place by conveying essential information without redundancy. The structure is efficient and well-organized for a destructive operation.

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 destructive tool with no annotations and no output schema, the description does an excellent job covering the critical aspects: purpose, irreversible nature, failure conditions, and prerequisites. It could be slightly more complete by mentioning authentication or response format, but given the context, it provides sufficient guidance for safe usage.

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%, with the parameter 'name' documented as 'Name of the option set to delete'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. The baseline score of 3 is appropriate since the schema already fully describes the parameter.

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 action ('permanently deletes') and resource ('an option set from Dataverse'), making the purpose specific and unambiguous. It distinguishes from siblings like 'delete_dataverse_column' or 'delete_dataverse_table' by specifying the resource type as 'option set'.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('Ensure no columns reference this option set before deletion') and when it will fail ('if the option set is being used by any columns'). It also implicitly contrasts with alternatives like 'update_dataverse_optionset' by emphasizing the irreversible nature of deletion.

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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