Acumatica MCP Server

get_schema

Discover user-defined extension fields and view names for any Acumatica entity, enabling custom field retrieval via the custom parameter.

Instructions

Return the entity's extension-field schema (GET /{Entity}/$adHocSchema).

Two reasons to call this:

Discover user-defined extension fields (UsrXxx fields, attribute fields like AttributeCOLOR) that are NOT in the standard contract and not listed by describe_entity(). These appear nested under a view name in the response.
Discover the available VIEW NAMES for this entity's graph. View names are the first part of the 'ViewName.FieldName' string needed by the custom= parameter. Standard Acumatica DAC fields (e.g. CreatedByID, LastModifiedByID) that are absent from the contract can ALSO be pulled via custom= using these view names, even though they don't appear explicitly in this schema response.

Common SalesOrder view names (confirmed working): Document - SOOrder header fields (CreatedByID, BranchID, etc.) CurrentDocument - additional header computed fields Transactions - line-level fields (on Details rows) Adjustments - payment application fields

Example workflow: 1. get_schema("SalesOrder") # identify view names 2. list_records("SalesOrder", # pull extension + standard DAC fields custom="Document.CreatedByID,Document.UsrYourCustomField")

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": "<entity>"
    },
    "name": "get_schema"
  }
}

Input Schema

Name	Required	Description	Default
`entity`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 10, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description fully carries the behavioral transparency burden. It explains the response structure (nested under view names), mentions that standard DAC fields absent from the contract can still be pulled via custom=, and provides common view names. 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?

The description is well-structured with bullet points and an example, and is front-loaded with the purpose. It is slightly verbose but every part adds value. Could be slightly more concise, but still effective.

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 existence of an output schema, the description does not need to explain return values. It is complete for the tool's purpose, covering what it returns, why to use it, and how to use the results with other tools like list_records.

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 only parameter 'entity' has no schema description coverage, but the description adds meaning by giving usage context, examples (e.g., 'SalesOrder'), and explaining that it is the entity name. It adds value beyond the raw schema.

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 that the tool returns the entity's extension-field schema, and distinguishes it from siblings like describe_entity and list_records by explaining it discovers user-defined fields and view names not in the standard contract.

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?

The description explicitly lists two reasons to call the tool and provides an example workflow. It also implicitly tells when not to use it (e.g., for standard contract fields, use describe_entity) and mentions alternatives like describe_entity().

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

Deploy Server