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Dataverse MCP Server

by mwhesse

Get Dataverse Solution

get_dataverse_solution

Retrieve detailed solution information including metadata, version, publisher details, and configuration to inspect solution properties and understand solution structure in Microsoft Dataverse.

Instructions

Retrieves detailed information about a specific solution including its metadata, version, publisher details, and configuration. Use this to inspect solution properties and understand solution structure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uniqueNameYesUnique name of the solution to retrieve

Implementation Reference

  • The core handler function for the 'get_dataverse_solution' tool. It queries the Dataverse API for the solution by uniqueName using an OData filter and expand for publisher details, formats the response, and handles errors appropriately.
    async (params) => {
      try {
        const result = await client.get(
          `solutions?$filter=uniquename eq '${params.uniqueName}'&$expand=publisherid($select=friendlyname,uniquename,customizationprefix,customizationoptionvalueprefix)`
        );
    
        if (!result.value || result.value.length === 0) {
          throw new Error(`Solution with unique name '${params.uniqueName}' not found`);
        }
    
        return {
          content: [
            {
              type: "text",
              text: `Solution information for '${params.uniqueName}':\n\n${JSON.stringify(result.value[0], null, 2)}`
            }
          ]
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: `Error retrieving solution: ${error instanceof Error ? error.message : 'Unknown error'}`
            }
          ],
          isError: true
        };
      }
    }
  • The tool schema definition including title, description, and Zod inputSchema validating the uniqueName parameter.
    {
      title: "Get Dataverse Solution",
      description: "Retrieves detailed information about a specific solution including its metadata, version, publisher details, and configuration. Use this to inspect solution properties and understand solution structure.",
      inputSchema: {
        uniqueName: z.string().describe("Unique name of the solution to retrieve")
      }
    },
  • The exported getSolutionTool function that registers the 'get_dataverse_solution' MCP tool with the server, including schema and handler.
    export function getSolutionTool(server: McpServer, client: DataverseClient) {
      server.registerTool(
        "get_dataverse_solution",
        {
          title: "Get Dataverse Solution",
          description: "Retrieves detailed information about a specific solution including its metadata, version, publisher details, and configuration. Use this to inspect solution properties and understand solution structure.",
          inputSchema: {
            uniqueName: z.string().describe("Unique name of the solution to retrieve")
          }
        },
        async (params) => {
          try {
            const result = await client.get(
              `solutions?$filter=uniquename eq '${params.uniqueName}'&$expand=publisherid($select=friendlyname,uniquename,customizationprefix,customizationoptionvalueprefix)`
            );
    
            if (!result.value || result.value.length === 0) {
              throw new Error(`Solution with unique name '${params.uniqueName}' not found`);
            }
    
            return {
              content: [
                {
                  type: "text",
                  text: `Solution information for '${params.uniqueName}':\n\n${JSON.stringify(result.value[0], null, 2)}`
                }
              ]
            };
          } catch (error) {
            return {
              content: [
                {
                  type: "text",
                  text: `Error retrieving solution: ${error instanceof Error ? error.message : 'Unknown error'}`
                }
              ],
              isError: true
            };
          }
        }
      );
    }
  • src/index.ts:169-169 (registration)
    The invocation in the main index.ts that calls getSolutionTool to register the tool with the MCP server instance and Dataverse client.
    getSolutionTool(server, dataverseClient);
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates this is a read operation ('retrieves'), but it doesn't cover critical aspects like authentication requirements, rate limits, error handling, or whether it's idempotent. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 efficiently structured in two sentences: the first states the purpose and scope, and the second provides usage guidance. Every word earns its place, with no redundancy or fluff, making it easy to parse and understand quickly.

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

Completeness3/5

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

Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and usage but lacks behavioral details (e.g., permissions, errors) and doesn't explain the return format, which is problematic since there's no output schema. This leaves the agent with gaps in fully understanding the tool's operation.

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?

The input schema has 100% description coverage, with 'uniqueName' clearly documented as 'Unique name of the solution to retrieve.' The description adds no additional parameter details beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 tool's purpose with specific verbs ('retrieves detailed information') and resources ('specific solution'), and it lists the types of information returned (metadata, version, publisher details, configuration). However, it doesn't explicitly differentiate from sibling tools like 'list_dataverse_solutions' or 'get_solution_context', which reduces clarity in a crowded toolset.

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 provides implied usage guidance by stating 'Use this to inspect solution properties and understand solution structure,' which suggests it's for detailed examination rather than listing. However, it lacks explicit when-to-use vs. when-not-to-use instructions or named alternatives (e.g., compared to 'list_dataverse_solutions' for a high-level overview), leaving some ambiguity.

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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