FlexSim MCP Server

get_node

Read a FlexSim model tree node value by path or object name and return it as JSON, including numbers, strings, and composite arrays.

Instructions

读取模型树节点值，返回 JSON（数字/字符串/复合数组）。路径大小写敏感；对象名（如 Q1）或完整路径（如 Tools/ModelUnits/ModelDateTimes/startTime/dateString）均可。

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": {
      "path": "<path>"
    },
    "name": "get_node"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes	节点路径或对象名

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2Nov 7, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations present, the description carries the full behavioral burden. It usefully discloses that the return value is JSON with number/string/compound-array shapes and that the path is case-sensitive, but it says nothing about what happens when a path is missing, whether an open model is required, or whether access is restricted.

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?

Two compact clauses with zero waste: what it returns first, then the path rules with inline examples. Nothing is repeated and the constraints are front-loaded before the caller commits to a path argument.

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 single-parameter read tool with no annotations, the definition covers the essential gaps: return type, path formats, and case sensitivity. What remains thin is failure behavior when a path does not resolve, which matters for a tool with no output schema to fall back on.

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 description coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the generic "节点路径或对象名" label: it gives a concrete object-name example (Q1) and a full path example (Tools/ModelUnits/ModelDateTimes/startTime/dateString), plus the case-sensitivity rule that the schema omits entirely.

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?

The description opens with a specific verb+resource, "读取模型树节点值" (read model tree node value), which clearly separates it from write_node, add_node, rename_node and delete_object among the siblings. It never names those alternatives explicitly, so it stops short of a 5, but an agent can still tell what this tool does without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: read a value that already exists in the model tree. There is no explicit statement of when to prefer this over list_tree or get_target, and no mention of preconditions such as an open model, which matters given siblings like open_model and select_target.

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