Pagelensai MCP Server

PageLens AI — MCP Server

AI agents can run senior-level website audits in seconds.

An MCP (Model Context Protocol) server that gives AI agents direct access to PageLens AI — automated website reviews covering UX, SEO, Performance, Accessibility, Security, and Conversion.

Plug it into Cursor, Claude, or any MCP-compatible client and your agent can read scan results, drill into findings, surface quick wins, and close the fix loop — all without leaving the IDE.

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MCP Endpoint

https://www.pagelensai.com/api/mcp

This is a remote MCP server — no local install required.

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Quick Start

Cursor

Add to your ~/.cursor/mcp.json (or workspace .cursor/mcp.json):

{
  "mcpServers": {
    "pagelens": {
      "url": "https://www.pagelensai.com/api/mcp"
    }
  }
}

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "pagelens": {
      "url": "https://www.pagelensai.com/api/mcp"
    }
  }
}

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Authentication

This server uses OAuth 2.0. Your MCP client will open a browser window to authorize with your PageLens account on first connect. No API keys to manage.

Scopes granted on authorization:

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Available Tools

whoami

Confirm which PageLens account this MCP session is operating on, plus granted OAuth scopes.

{}

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list_domains

List the domains you've verified ownership of, along with badge tier and the scan currently anchored to the public badge.

{
  "include_unverified": false
}

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list_scans

List your most recent PageLens scans. Filter by status, domain, or date. Returns a slim summary per scan (id, URL, score, grade, severity counts).

{
  "limit": 20,
  "status": "COMPLETE",
  "domain": "example.com",
  "since": "2026-01-01T00:00:00Z"
}

Status values: PENDING · RUNNING · COMPLETE · FAILED · CANCELLED

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get_scan

Read the full summary for a single scan: score, grade, severity counts, executive summary, top-5 highest-priority findings, and per-persona reviews.

{
  "scan_id": "clxxxxxxxxxxxxxxx"
}

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list_findings

Page through all findings for a scan. Filter by severity, category, persona, page URL, or rule ID. Use format: "full" to include descriptions, suggestions, and evidence.

{
  "scan_id": "clxxxxxxxxxxxxxxx",
  "severity": "HIGH",
  "category": "SECURITY",
  "format": "full",
  "limit": 50
}

Severity levels: CRITICAL · HIGH · MEDIUM · LOW · INFO

Categories: UX · SEO · PERFORMANCE · ACCESSIBILITY · SECURITY · CONTENT · HEADERS · DESIGN · ERROR

Personas: MARKETER · CRO · UX · ACCESSIBILITY · BRAND · EXECUTIVE · PERFORMANCE · SEO

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get_quick_wins

Return the top N quick-win findings — high impact, low-to-moderate effort — ranked by the same Impact × Effort scorer used in the PageLens dashboard. Optionally override the scan's preset to re-rank under a different lens.

{
  "scan_id": "clxxxxxxxxxxxxxxx",
  "limit": 5,
  "preset_override": "CONVERSION"
}

Presets: PRE_SALES · PRE_LAUNCH · CONVERSION · INVESTOR · BRAND_POLISH

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report_finding_feedback

Flag a finding as a false positive, wrong severity, wrong category, or not actionable. Requires a paragraph of reasoning and a concrete evidence snippet.

{
  "finding_id": "clxxxxxxxxxxxxxxx",
  "kind": "FALSE_POSITIVE",
  "reason": "The selector .pointer-events-auto matches 100+ utility classes, not a single offending element.",
  "evidence": "<div class=\"pointer-events-auto ...\"> — Tailwind utility, not an event-handler.",
  "proposed_severity": "LOW"
}

Feedback kinds: FALSE_POSITIVE · INCORRECT_SEVERITY · INCORRECT_CATEGORY · NOT_ACTIONABLE · OTHER

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What PageLens Checks

Each scan runs a deterministic rule engine + AI reviewer pipeline across every page:

Findings include severity, effort estimate, copy-pasteable evidence, and a one-line fix suggestion.

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Example Agent Workflows

Pre-launch audit in Cursor:

"Run PageLens on my staging site, list all CRITICAL and HIGH findings, and create GitHub issues for the top 5."

CRO review:

"Fetch the latest scan for example.com, get the CONVERSION quick wins, and summarise what to fix before the campaign launch."

Security sweep:

"List all SECURITY findings with severity HIGH or above from my last scan and show me the evidence for each."

Post-fix validation:

"After I've fixed the findings, start a new scan and compare the score to the previous one."

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Pricing

PageLens is pay-per-scan — no subscription required for one-off audits.

Every tier produces the same full report — Starter through Professional differ only by page-count cap, not report depth. The Monitor subscription runs weekly scans automatically and surfaces drift between runs.

See full pricing →

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Links

• Website: https://www.pagelensai.com
• MCP endpoint: https://www.pagelensai.com/api/mcp
• Dashboard: https://www.pagelensai.com/dashboard
• GitHub: https://github.com/PageLens-AI/pagelensai-mcp-server
• MCP docs: https://www.pagelensai.com/mcp

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License

MIT © PageLens AI