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Path of Building MCP Server

Path of Building MCP Server

by urbanvcode
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

suggest_optimal_nodes

Recommends passive skill nodes for a Path of Building character based on the chosen damage, defense, life, energy shield, or stat goal and available passive points.

Instructions

AI-powered suggestion of optimal passive nodes based on build goals

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": {
      "build_name": "<build_name>",
      "goal": "<goal>"
    },
    "name": "suggest_optimal_nodes"
  }
}

Input Schema

NameRequiredDescriptionDefault
goalYesOptimization goal: 'damage', 'defense', 'life', 'es', or stat name
build_nameYesBuild to optimize
points_availableNoNumber of passive points to spend (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden. It mentions 'AI-powered' hinting at probabilistic behavior but does not disclose whether it is read-only, requires an existing build, or what the response format is. This is insufficient for safe invocation.

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?

One sentence, no redundant information, and gets to the point immediately. The description is appropriately sized and front-loaded.

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

Completeness2/5

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

For a tool with no output schema and no annotations, the description is too brief. It fails to mention return value, prerequisites, or how it differs from optimize_tree, making it incomplete for an AI agent to decide when to use it.

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%, so the schema documents all parameters. The description adds little beyond mentioning 'build goals' which aligns with the goal parameter, but it does not explain the meaning of points_available or build_name beyond the schema, so it meets the baseline.

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 clearly states the tool suggests optimal passive nodes based on build goals, using a specific verb and resource. However, it does not distinguish from sibling tools like optimize_tree or analyze_build, so it lacks explicit sibling differentiation.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as optimize_tree or analyze_build. The description only states the purpose without context, prerequisites, or exclusions.

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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