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ALM X++ MCP Server

by io.github.alimbenhelal-pro

dmf

Consolidated Data Management Framework tool — one entry point for all 5 DMF operations, selected via action. Each action forwards to the exact same implementation as its dedicated tool (dmf_import_file / dmf_create_data_project / dmf_apply_entity_filter / dmf_export_package / dmf_get_job_status) — identical behavior and validation, just one tool schema instead of five. The dedicated tools remain available unchanged.

action="import" (= dmf_import_file): entityName, legalEntity, filePath OR csvContent, definitionGroupId?, execute?, overwrite?, pollTimeoutSeconds? action="create_project" (= dmf_create_data_project): projectName, entities, sourceName, operationType? ('Export' default or 'Import') action="apply_filter" (= dmf_apply_entity_filter): projectName, entityRowName, aotEntityName, fieldName, filterValue action="export" (= dmf_export_package): definitionGroupId, legalEntity, packageName?, reExecute?, pollTimeoutSeconds? action="status" (= dmf_get_job_status): executionId

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesimport | create_project | apply_filter | export | status
executeNoimport: execute after staging. Default true.
entitiesNocreate_project: comma-separated DMF entity names.
filePathNoimport: path to a .csv file on disk (or use csvContent).
fieldNameNoapply_filter: field to filter on, e.g. 'VendorAccountNumber'.
overwriteNoimport: overwrite existing project definition. Default true.
reExecuteNoexport: re-execute the project. Default true.
csvContentNoimport: inline CSV content (or use filePath).
entityNameNoimport: target DMF entity name, e.g. 'Customers V3'.
sourceNameNocreate_project: existing DMF source data format name.
executionIdNostatus: the executionId returned by an import or export action.
filterValueNoapply_filter: value or wildcard to match.
legalEntityNoimport/export: legal entity / company id, e.g. 'USMF'.
packageNameNoexport: optional package name.
projectNameNocreate_project/apply_filter: DMF project name.
aotEntityNameNoapply_filter: AOT entity name, e.g. 'VendVendorV2Entity'.
entityRowNameNoapply_filter: entity row label, e.g. 'Vendors V2'.
operationTypeNocreate_project: 'Export' (default) or 'Import'.
definitionGroupIdNoimport/export: definitionGroupId (DMF project id).
pollTimeoutSecondsNoimport/export: max seconds to poll for completion. Default 300.

TDQS

A4.1/5.0
Behavior3/5

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

Annotations only provide `readOnlyHint: false`, so the description carries most of the burden. It usefully discloses that each action forwards to the exact same implementation and validation as the corresponding dedicated tool. However, it does not directly describe side effects like overwriting projects, return payloads, error behavior, or polling semantics beyond naming `pollTimeoutSeconds`.

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 purpose is front-loaded, and each action is described in a compact, scannable line. The length is justified by the dispatcher design with 5 operations and 20 parameters, and there is no filler.

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

Completeness3/5

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

Action selection and parameter mapping are well covered, which is the core invocation need. However, with no output schema, the description should more directly state what each action returns, such as execution IDs or status payloads; it largely relies on the assertion that behavior is identical to the dedicated tools.

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?

Schema coverage is 100%, so the baseline is 3; the description adds real value by grouping the 20 flat parameters by action and marking optional ones with `?`. It also makes the `filePath OR csvContent` alternative explicit, which is not obvious from the schema alone.

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 immediately states it is a consolidated entry point for all 5 DMF operations, maps each `action` value to a named dedicated tool, and lists the exact parameter sets per action. This is specific about verb, resource, and scope, and cleanly distinguishes it from the five `dmf_*` sibling tools.

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?

It says the tool is the 'one entry point' for all five DMF operations and notes that dedicated tools remain available unchanged, which tells an agent how this tool relates to its alternatives. It does not explicitly state when to prefer the consolidated tool over a dedicated one, but the claim of identical behavior makes the choice low-risk.

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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