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ALM X++ MCP Server

by io.github.alimbenhelal-pro

get_data_entity_info

Read-onlyIdempotent

WHEN: developer building an OData / DMF integration needs a quick rundown of a specific data entity: its public OData name, datasources, key fields, and IsPublic status. Triggers: 'data entity info', 'OData entity details', 'is X a public entity', 'entity datasources'. Cloud-safe: pure metadata read from the KB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNameYesData entity name (AxDataEntityView), e.g. 'CustCustomerV3Entity', 'SalesOrderHeaderV2Entity'.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds value by stating it is Cloud-safe and a pure metadata read from the KB, reinforcing the non-mutating nature and providing context about the data source.

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 compact and front-loaded with the key WHEN context, followed by useful trigger phrases and a safety note. Every element earns its place, and there is no filler.

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?

This is a simple read-only tool with one well-documented parameter and no output schema. The description explicitly lists what the tool returns, making it complete enough for an agent to select and invoke it correctly.

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 coverage is 100% and the single parameter is already well-described with an example. The description adds no additional parameter-level detail, so the schema carries the burden and the baseline of 3 is appropriate.

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 the tool retrieves metadata for a specific data entity: public OData name, datasources, key fields, and IsPublic status. It distinguishes itself from sibling tools by scoping to entity metadata lookups for OData/DMF integration contexts.

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 an explicit WHEN condition and trigger phrases, making it clear when an agent should use this tool. It does not explicitly name alternatives or when-not-to-use scenarios, but the context is sufficiently clear.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes and clear triggers, reducing ambiguity. For example, PR-related tools are separated into analysis, listing, commenting, and dependency mapping. However, some overlap exists between find_references, find_extensions, and find_callers, which could confuse an agent without careful descriptions.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with verb_noun structure within subgroups (e.g., ado_*, find_*, search_*, generate_*). There is no mixing of camelCase or other styles, though the variety of prefixes slightly reduces predictability.

Tool Count3/5

With 38 tools, the server feels slightly over-scoped for its domain. While each tool has a specific function, the number is high compared to typical well-scoped servers (10-15 tools). Some tools like find_references and find_callers could be consolidated.

Completeness4/5

The tool set covers a broad range of D365 F&O development and DevOps tasks, including code search, analysis, security, performance, upgrades, and work item management. Minor gaps exist, such as the absence of direct object modification or batch job management, but the core workflows are well covered.

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