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midas-nx-mcp

midas-nx-mcp

by Dennis5882

apply_operations

Destructive

Runs a previewed batch of create, update, and delete operations across multiple model tables in dependency order, then applies them step by step.

Instructions

Create, update and delete records in several tables at once, e.g. the materials, sections, nodes, elements, load cases and loads of a small model. Two steps: preview, then apply.

Each operation is what write_records or delete_records would take: table, action ("create", "update" or "delete"), and records ({id: fields}) or ids. The steps are run in midas-nx's dependency order (deletes first, then what is named before what names it), whatever order they are given in; the preview shows that order. The preview checks the whole batch first, with the records earlier steps create counted as existing: the same rules as write_records and delete_records. A UNIT change is not taken here. At most 20 operations and 200 records in all.

Applying runs the steps one by one and reads each table back. It stops at the first step that fails, changes nothing, or stores new records under other ids while a later step names that table; what was already applied stays (nothing is rolled back) and the result lists the steps done, the failed one, and the ones not run. Any change discards the analysis results.

Input Schema

NameRequiredDescriptionDefault
productYes
operationsYes
confirm_tokenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, yet the description adds substantial context: dependency ordering of steps, full-batch validation in preview, stop-at-first-failure, no rollback ("what was already applied stays"), and that analysis results are discarded. The notable omission is how preview versus apply is actually signalled — the two-step protocol is never tied to the confirm_token parameter that implements it.

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?

Purpose and the two-step model are front-loaded, followed by ordering, validation, limits, and failure semantics in a logical sequence. Dense but every sentence carries operational information; no filler.

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

Completeness4/5

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

For a destructive batch mutation with no output schema, the description covers ordering, limits, failure behavior, and even the shape of the result (steps done, failed step, steps not run). The remaining gaps — meaning of `product` and the confirm_token preview/apply mechanism — are real but narrow.

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 reported as 0%, so the description must compensate; it does explain the Operation shape (table, action, records as {id: fields}, or ids) and anchors it to write_records/delete_records. However, it says nothing about the top-level `product` enum (gen/civil) or `confirm_token`, leaving two of three parameters semantically unexplained.

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?

States a specific verb set (create/update/delete) against a specific resource (records in several tables at once), with concrete examples (materials, sections, nodes, elements, load cases, loads). It is clearly distinguishable from the per-call siblings write_records and delete_records, which it names as the single-step equivalents.

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?

Establishes the workflow explicitly ("Two steps: preview, then apply"), states the batch limits (20 operations, 200 records) and one exclusion ("A UNIT change is not taken here"). It does not explicitly say when to prefer write_records/delete_records over this tool, so the choice between batch and single-call paths is left to inference.

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