open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/accesslint-mcp
Description: MCP server for accessible agentic coding — WCAG audit tools for AI coding agents
Latest version: 0.2.5

# @accesslint/mcp

MCP server for accessible agentic coding — WCAG audit tools for AI coding agents. Built on [@accesslint/core](https://github.com/AccessLint/core). From [AccessLint](https://www.accesslint.com).

## Setup

Add to your MCP client configuration:

```json
{
  "mcpServers": {
    "accesslint": {
      "command": "npx",
      "args": ["@accesslint/mcp"]
    }
  }
}
```

## Tools

- **audit_html** — Audit an HTML string for WCAG violations. Auto-detects fragments vs full documents.
- **audit_file** — Read an HTML file from disk and audit it.
- **audit_url** — Fetch a URL and audit the returned HTML.
- **diff_html** — Audit new HTML and diff against a previously named audit to verify fixes.
- **list_rules** — List available WCAG rules with optional filters by category, level, fixability, or criterion.
All audit and diff tools accept an optional `min_impact` parameter to filter results by severity. Valid values, from most to least severe: `critical`, `serious`, `moderate`, `minor`. When set, only violations at that level or above are shown.

Each violation in the audit output includes the rule ID, CSS selector, failing HTML, impact level, and — where available — a concrete fix suggestion, fixability rating, and guidance. When multiple elements break the same rule, shared metadata is printed once to keep output compact.

## Prompts

### React Component Auditing

To audit React components (`.jsx`/`.tsx`), the agent uses the `audit-react-component` prompt, which guides it through:

1. Reading the component source
2. Mentally rendering it to static HTML (acting as `renderToStaticMarkup`)
3. Passing the rendered HTML to `audit_html` with `component_mode: true`

No extra runtime dependencies are required — the agent renders the component itself based on the source code.

## Why use this instead of prompting alone?

Without tools, the agent reasons about WCAG rules from memory. The MCP replaces that with structured output — specific rule IDs, CSS selectors, and fix suggestions — so the agent skips straight to applying fixes. This means 23% fewer output tokens per run, which translates directly to faster and cheaper completions.

Benchmarked across 25 test cases, 67 fixable violations, 3 runs each (Claude Opus):

| | With @accesslint/mcp | Agent alone |
|---|---|---|
| **Violations fixed** | 99.5% (200/201) | 93.5% (188/201) |
| **Regressions** | 1.7 / run | 2.0 / run |
| **Cost** | $0.56 / run | $0.62 / run |
| **Duration** | 270s / run | 377s / run |
| **Timeouts** | 0 / 63 tasks | 2 / 63 tasks |

## License

MIT