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KiCad MCP Server (IPC API)

KiCad MCP Server (IPC API)

by lmaag182
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_dimensions

List all dimension objects in the KiCad board to view or verify measurements and annotations.

Instructions

List all dimension objects.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_dimensions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are present, and the description does not disclose any behavioral traits such as output format, performance implications, or whether it requires specific permissions. The agent has no insight into side effects or constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at four words, front-loading the purpose. However, it may be overly terse, missing opportunities to add helpful context without becoming verbose.

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?

Given the complexity (many sibling list tools) and the presence of an output schema, the description should clarify what a 'dimension object' is and how this tool differs from related lists. Currently, it is insufficiently complete for an AI agent to reliably distinguish it.

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 input schema has no parameters and is fully covered by the description (100% coverage). Since there are no parameters to explain, the description adds no param-level details, which is adequate given 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 it lists all dimension objects, using a specific verb and resource. However, it does not differentiate from many sibling list tools (list_components, list_nets, etc.), leaving ambiguity about what 'dimensions' specifically refers to.

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. The description does not mention context, prerequisites, or distinctions from other list tools, leaving the agent to infer usage.

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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