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aura-components-mcp

aura_search_all

Search free Aura components, skills, assets, and design systems in one parallel query. Returns slim excerpts by default and per-surface fallback/status fields so you can read mixed results correctly.

Instructions

One call across components, skills, assets, and design systems in parallel. Free only. Slim rows by default (excerpts, no blobs). Each surface runs its own fallback pipeline, so mixed outcomes are normal (skills may fall back while components go honestly empty) — read isFallback/no_match per surface, not once globally.

Input Schema

NameRequiredDescriptionDefault
slimNo
limitNo
queryNo
themeNo
min_viewsNo
exact_matchNo
negative_themeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.7.3
    • addedInput schema / properties / exact_match
      Added value: +{
      +  "type": "boolean"
      +}
    • addedInput schema / properties / min_views
      Added value: +{
      +  "type": "number"
      +}
    • addedInput schema / properties / negative_theme
      Added value: +{
      +  "enum": [
      +    "dark",
      +    "light"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / properties / slim
      Added value: +{
      +  "type": "boolean"
      +}
    • addedInput schema / properties / theme
      Added value: +{
      +  "enum": [
      +    "dark",
      +    "light"
      +  ],
      +  "type": "string"
      +}
  2. First observedv1.2.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does well: it discloses the 'Free only' filter, the default slim/excerpt response shape with no blobs, and the per-surface fallback semantics with the instruction to read isFallback/no_match per surface rather than globally. That last point is unusually valuable operational context. It stops short of describing auth needs, rate limits, or result ordering.

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?

Three dense, front-loaded sentences with no filler: purpose first, then scope constraint, then response-shape nuance, then the fallback caveat. The em-dash clause is information-dense, though the jargon ('honestly empty') is slightly informal for a spec.

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

Completeness3/5

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

No output schema and no annotations, so the description must cover both behavior and parameters. It handles the return-behavior nuances well (fallback, slim rows) but leaves all six non-slim parameters undefined and offers no explicit sibling routing. Adequate but with clear gaps given the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 7 parameters, and the description explains almost none of them. It gestures at 'slim rows by default,' which partially maps to the slim flag, but limit, query, theme, negative_theme, min_views, and exact_match are left entirely undocumented in both schema and description. This is a significant gap for a 7-param tool.

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 action (one parallel search call) over four named resource types (components, skills, assets, design systems). It clearly distinguishes itself from the four sibling per-surface search tools by being the fan-out aggregate. An agent can tell what this does and when it would supersede the singleton searches.

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?

The phrase 'One call across... in parallel' implies the fan-out use case, and 'Free only' establishes a scope constraint, which is real guidance. However, it never explicitly says when to prefer this over aura_search_components/skills/assets/design_systems, or whether the narrower tools are cheaper/more precise. Usage is implied rather than routed.

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