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ryanmichaeljames

Dataverse MCP Server

dataverse_query_table

Read-onlyIdempotent

Query records from any Dataverse table using OData filters, sorting, and expansion. Specify columns, filters, and related data to retrieve exactly what you need.

Instructions

Query records from a Dataverse table with OData filtering, ordering, and expansion.

For a single record by GUID use dataverse_get_record. For just a count use dataverse_count_records. For group-by aggregation use dataverse_aggregate_table. To create, update, or delete records use dataverse_create_record, dataverse_update_record, or dataverse_delete_record.

Always specify select to limit returned columns and keep payloads small.

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 and idempotentHint; description adds context about OData capabilities (filtering, ordering, expansion) and payload advice. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is two short paragraphs, front-loaded with purpose and usage. No redundant sentences, though could be slightly more streamlined.

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?

Given the tool's complexity and the presence of an output schema, the description covers main capabilities, sibling differentiation, and usage advice. Adequate completeness.

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?

Input schema provides detailed descriptions for all parameters (coverage 100%); description adds general advice on 'select' but does not enhance semantics beyond what schema already provides.

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 it queries records from a Dataverse table with OData filtering, ordering, and expansion. It distinguishes from siblings by explicitly naming alternatives for single records, counts, aggregation, and CRUD operations.

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?

Provides explicit guidance on when to use this tool vs alternatives (e.g., 'For a single record by GUID use dataverse_get_record') and advises on best practice ('Always specify select to limit returned columns').

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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