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A11y Expert MCP

A11y Expert MCP

by Elizabeth1979
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

review_code

Review HTML, JSX, TSX, Vue, or Svelte code for accessibility issues and get specific fix suggestions with WAI-ARIA pattern references.

Instructions

Review code for accessibility issues and suggest fixes.

Args:
    code: The HTML, JSX, TSX, Vue, or Svelte component code to review.
    component_type: Optional hint about what the component is
                    (e.g., "modal", "dropdown", "form").

Returns:
    Accessibility issues found with specific fix suggestions and
    references to WAI-ARIA patterns.

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": {
      "code": "<code>"
    },
    "name": "review_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYes
component_typeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, so description carries burden. It discloses the tool finds issues, suggests fixes, and references WAI-ARIA patterns. Lacks details on output format or edge cases, but adequate for an analysis tool.

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-line purpose followed by concise arg/return docs. Every sentence adds value, no wasted words. Front-loaded with main action.

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

Completeness5/5

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

Given the tool's simplicity (two params, returns issues), the description covers inputs and outputs sufficiently. With an output schema presumably available, full completeness is achieved.

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 coverage is 0%, so description must compensate. It adds context for 'code' (acceptable formats) and 'component_type' (examples like modal, dropdown), improving understanding beyond type alone.

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?

Clearly states 'Review code for accessibility issues and suggest fixes,' with a specific verb and resource. Differentiates from siblings (check_contrast, get_pattern, list_patterns) which focus on contrast or pattern 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?

Describes the context for use (reviewing code for accessibility) but does not explicitly state when not to use or suggest alternatives. Clear enough for an 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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