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ryanmichaeljames

Dataverse MCP Server

dataverse_list_custom_api_request_parameters

Read-onlyIdempotent

List request parameter records for a Dataverse Custom API by providing the parent API's GUID. Optionally filter results with an OData expression to narrow down specific parameters.

Instructions

List request parameter records for a Custom API.

Filters by custom_api_id (GUID) to return only parameters belonging to that Custom API. Returns customapirequestparameterid, uniquename, name, displayname, type, isoptional for each record. Type enum: 0=Boolean, 1=DateTime, 2=Decimal, 3=Entity, 4=EntityCollection, 5=EntityReference, 6=Float, 7=Integer, 8=Money, 9=Picklist, 10=String, 11=StringArray, 12=Guid. An optional OData filter expression can further narrow results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds value by listing returned fields and the type enum, but no additional behavioral traits are disclosed beyond what annotations imply.

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 three concise sentences with key information front-loaded: action, filter, return fields, and type enum. No waste.

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

Completeness5/5

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

Given the output schema exists, the description adequately covers purpose, filtering, and return data. The type enum mapping is particularly helpful. No gaps for a list tool.

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 already provides detailed descriptions for all parameters (top, filter, custom_api_id, dataverse_url). The description adds only marginal clarification (e.g., 'Filters by custom_api_id'), so baseline 3 is appropriate.

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 it lists request parameter records for a Custom API, with filtering by custom_api_id. However, it does not explicitly differentiate from closely related sibling tools like dataverse_list_custom_api_response_properties.

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 (e.g., filtering by custom_api_id) but does not provide explicit guidance on when to use this tool versus alternatives or when not to use it.

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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