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ryanmichaeljames

Dataverse MCP Server

dataverse_list_custom_apis

Read-onlyIdempotent

List Custom API records from a Dataverse environment. Use an OData filter to narrow results by properties like binding type, function status, or privacy.

Instructions

List Custom API records in the Dataverse environment.

Returns customapiid, uniquename, name, displayname, bindingtype, isfunction, isprivate, and allowedcustomprocessingsteptype for each record. Use the optional filter parameter to narrow results with an OData $filter expression (e.g., "isprivate eq false", "isfunction eq true"). bindingtype: 0=Global, 1=Entity, 2=EntityCollection. allowedcustomprocessingsteptype: 0=None, 1=AsyncOnly, 2=SyncAndAsync. Use dataverse_get_custom_api to fetch expanded request parameters and response properties for a specific Custom API.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe read operation. The description adds value by detailing the returned fields and providing enumeration mappings for bindingtype and allowedcustomprocessingsteptype, which are not in the schema. No contradictions with annotations.

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 five sentences that efficiently cover purpose, returned fields, filter usage with examples, enum mapping, and a sibling tool reference. No redundant or unnecessary text.

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?

The description sufficiently covers purpose, filter usage, and sibling tool. The schema handles parameter details and the output schema presumably covers return values. Minor omission: no mention of pagination via the top parameter, but it's documented in the schema. Overall, adequate for a list tool with good annotations and schema.

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?

The input schema provides descriptions for all three parameters, so the baseline is 3. The description goes beyond by giving concrete filter examples and explaining the numeric values for bindingtype and allowedcustomprocessingsteptype, which are not explained in the schema. Thus it adds meaningful semantic context.

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 starts with 'List Custom API records' which clearly specifies the verb and resource. It lists the specific fields returned, distinguishing it from sibling tools like dataverse_get_custom_api, which is explicitly mentioned for fetching detailed data for a single API. This makes the purpose highly specific and distinguishable.

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?

The description provides clear guidance on when to use the filter parameter with examples, and explicitly directs users to dataverse_get_custom_api for expanded details of a specific API. While it does not state when not to use this tool, the context is clear enough for the agent to make decisions.

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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