dataverse-mcp-server

add_attribute

Add a column to an existing Microsoft Dataverse table by defining its logical name, data type, and display name. Use it to extend table schemas with fields like text, numbers, dates, or picklists.

Instructions

Add a column (attribute) to an existing Dataverse table

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity_logical_name": "<entity_logical_name>",
      "attribute": "<attribute>"
    },
    "name": "add_attribute"
  }
}

Input Schema

Name	Required	Description	Default
`attribute`	Yes
`entity_logical_name`	Yes	Logical name of the entity

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.9.0Oct 3, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

Changed2 schema fields changedv0.7.1Aug 21, 2026

addedInput schema / properties / attribute / properties / global_option_set

Added value: +{
+  "description": "Picklist only: bind the column to an existing Global OptionSet by its set name (e.g. 'contoso_sourceset') so the column shares one org-wide list instead of a private copy. Mutually exclusive with options.",
+  "minLength": 1,
+  "type": "string"
+}

changedInput schema / properties / attribute / properties / options / description

Previous value: -"Options for Boolean (2 items: false=0, true=1) or Picklist types"New value: +"Options for Boolean (2 items: false=0, true=1) or Picklist types. Creates a Local OptionSet owned by this one column; mutually exclusive with global_option_set."

First observedv0.5.0Jul 31, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, yet it only implies a write via the word 'Add'. It says nothing about required Dataverse privileges, that the new column is immediately persisted to the table's schema, or that some choices (e.g. DateTimeBehavior) are effectively irreversible.

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?

A single front-loaded sentence with zero waste. It is efficient, though its brevity is closer to under-specification than to disciplined conciseness, which caps it below a 5.

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?

For a schema-mutating tool with a nested object parameter, no annotations and no output schema, the description omits permissions, side effects, error conditions, and any hint about how the required nested attribute fields must be combined. An agent cannot call this confidently from the description alone.

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?

Top-level schema coverage is only 50% (attribute has no description; entity_logical_name does), and the description contributes no parameter detail. However, the nested attribute object documents its own fields thoroughly, including mutual exclusivity of options vs global_option_set and defaults, so the schema largely 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?

States a specific verb+resource ('Add a column (attribute) to an existing Dataverse table'), which maps cleanly onto the tool name and distinguishes it in kind from delete_attribute and update_attribute. It does not name or contrast those siblings explicitly, but the operation is unambiguous.

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?

No when-to-use guidance, no mention of prerequisites (the table must already exist, the attribute logical name must be unique), and no routing to alternatives such as update_attribute for modifying an existing column or add_picklist_option for extending a choice list.

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