Pagelensai MCP Server

Plug it into Cursor, Claude Desktop, Codex, or any MCP-compatible client and your agent can read scan results, drill into findings, surface quick

Local serverstdio

What is the Pagelensai MCP server?

Pagelensai MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Plug it into Cursor, Claude Desktop, Codex, or any MCP-compatible client and your agent can read scan results, drill into findings, surface quick wins, record owner decisions, and help close the fix loop without leaving the IDE.

What the assistant can call

Once Pagelensai is connected, these are the calls the assistant has available:

  • Cursor — The Cursor tool exposed by this server
  • whoami — Confirm which PageLens account this MCP session is operating on, plus granted OAuth scopes
  • list_domains — List the domains you've verified ownership of, along with badge tier and the scan currently anchored to the public badge
  • 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, and
  • get_scan — Read the full summary for a single scan: score, grade, owner-first launchVerdict, severity counts, launch context, executive summary, top-5
  • 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
  • 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
  • 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
  • acknowledge_finding_decision — Attach owner-controlled context to a finding when the issue is real, but reflects an intentional architecture, security, or product tradeoff
  • clear_finding_decision — Clear a previously acknowledged decision so it stops appearing on current and future reports. The audit history is preserved

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

Choosing this one

Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Pagelensai's toolset — Cursor, whoami, list_domains and 7 more — is a fair guide to whether it matches your workflow. It is maintained by pagelens-ai; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 10 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Pagelensai.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the pagelensai mcp server does with a few real requests.

Available tools

ToolWhat it does
CursorThe Cursor tool exposed by this server.
whoamiConfirm which PageLens account this MCP session is operating on, plus granted OAuth scopes.
list_domainsList the domains you've verified ownership of, along with badge tier and the scan currently anchored to the public badge.
list_scansList your most recent PageLens scans. Filter by status, domain, or date. Returns a slim summary per scan (id, URL, score, grade, severity counts, and launchVerdict). Scans may include launchContext with builderPlatform a
get_scanRead the full summary for a single scan: score, grade, owner-first launchVerdict, severity counts, launch context, executive summary, top-5 highest-priority findings, and per-persona reviews. For QA Audit scans, get_scan
list_findingsPage 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.
get_quick_winsReturn 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 len
report_finding_feedbackFlag a finding as a false positive, wrong severity, wrong category, or not actionable. Requires a paragraph of reasoning and a concrete evidence snippet.
acknowledge_finding_decisionAttach owner-controlled context to a finding when the issue is real, but reflects an intentional architecture, security, or product tradeoff.
clear_finding_decisionClear a previously acknowledged decision so it stops appearing on current and future reports. The audit history is preserved.

Example prompts to try

  • Use Pagelensai to Cursor.
  • Use Pagelensai to whoami.
  • Use Pagelensai to list domains.

Frequently asked questions

It connects Pagelensai to MCP-compatible AI assistants such as Claude and Cursor, exposing 10 tools (Cursor, whoami, list_domains, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Pagelensai directly.