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rededis

dataverse-mcp-server

by rededis

create_relationship

Create a relationship between two Dataverse tables by specifying OneToMany or ManyToMany, primary and related entities, and schema name.

Instructions

Create a relationship between two Dataverse tables

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesRelationship type
lookup_nameNoLogical name for lookup attribute (OneToMany only)
schema_nameYesUnique schema name for the relationship
primary_entityYesPrimary (referenced) entity logical name
related_entityYesRelated (referencing) entity logical name
lookup_display_nameNoDisplay name for lookup attribute (OneToMany only)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.9.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.5.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it discloses nothing beyond the implied mutation. It does not mention required privileges, whether the relationship can be removed (no delete_relationship sibling exists), what happens if the relationship already exists, or the implications of choosing a relationship type.

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?

The description is a single efficient sentence with zero waste and the core action front-loaded. It is concise, though arguably too terse for a six-parameter metadata mutation tool, keeping it just below a perfect score.

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

Completeness2/5

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

Given the absence of annotations and no output schema, the description should compensate with behavioral and usage context. Instead it provides only a one-line purpose, leaving significant gaps around permissions, reversibility, and relationship-type implications for an agent to infer.

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%, so the schema already documents all six parameters, including the OneToMany-only nature of lookup_name and lookup_display_name and the enum for type. The description adds no additional parameter meaning, which matches the baseline of 3 when the schema does the heavy lifting.

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 states a specific verb ('Create') and resource ('relationship between two Dataverse tables'), making the tool's purpose immediately clear. It does not, however, explicitly differentiate this tool from siblings like add_attribute or create_entity, so it falls short of the 5-level criterion for sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no when-to-use guidance, prerequisites, or alternatives. It does not say when to choose OneToMany versus ManyToMany, nor when to use this tool instead of manually adding attributes. This is a bare purpose statement with no usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.