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Understand-Anything MCP Server

Understand-Anything MCP Server

by VIethoangnguyenle
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_node_detail

Get full details of a specific node by its ID, including path, layer, tags, and complexity. Use query_nodes to find the ID first.

Instructions

Get full details of a specific node by its ID.

Args: node_id: Unique node ID (e.g., "upstream:function:src/auth/login.ts::loginUser"). Use query_nodes to find IDs. project: Project name. Leave empty if only one project.

Returns: Complete node details including path, layer, tags, complexity.

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": {
      "node_id": "<node_id>"
    },
    "name": "get_node_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
node_idYes
projectNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return content ('Complete node details including path, layer, tags, complexity') and implies a read-only operation via 'Get'. However, it does not mention error behavior, authentication, or rate limits, leaving some transparency gaps.

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 concise and well-structured with Args and Returns sections. The opening sentence states the purpose, the example adds immediate clarity, and every line contributes useful information without padding.

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?

The tool is relatively simple (2 parameters, output schema present), and the description covers the essential semantics, return content, and ID-finding workflow. It is complete enough for an agent to invoke correctly, though it could mention error cases or multi-project disambiguation more explicitly.

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 schema has no parameter descriptions (0% coverage), but the description fully compensates: node_id is explained with a concrete example ('upstream:function:src/auth/login.ts::loginUser') and pointer to query_nodes, while project is clarified with a conditional rule. This adds significant meaning beyond the bare schema fields.

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 'Get full details of a specific node by its ID,' which identifies the action (get), resource (node), and scope (specific node). This distinguishes it from siblings like query_nodes (search) and get_node_source (source code retrieval).

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 clear usage context: it instructs to 'Use query_nodes to find IDs' and explains the project parameter's conditionality ('Leave empty if only one project'). It does not explicitly exclude alternatives, but it gives actionable when-to-use guidance.

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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