"Information about web scraping or crawling" matching MCP connectors:

Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.

Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.

The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.

The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.

Real-time web analytics for AI agents: query traffic, funnels, revenue, and manage your sites.

Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.

Read-only access to your Nexly web analytics: traffic, pages, acquisition, events, and reports.

Privacy-first, cookie-free web analytics: create sites, install and verify tracking, read stats.

Uptime, SSL, DNS and domain monitoring you can talk to from Claude or any MCP client.

Mobile observability for AI agents. Investigate crashes, hangs, ANRs, bugs, and app performance, and triage app store reviews, directly from your IDE or terminal.

RUM platform for web performance analytics, Core Web Vitals, and third-party script monitoring.

Log, evaluate, and ground AI decisions against authority context. Returns PASS, WARN, or BLOCK.

Real User Monitoring for Core Web Vitals. Query LCP, INP, CLS field data from real visitors.

Website performance monitoring: scans, Core Web Vitals, RUM data and alerts.

Structural observability for AI conversations. Detects loops, stuck states, breakthroughs, and convergence across 17 channels without analyzing content.

The Polar Signals MCP server enables AI assistants to connect directly with performance profiling data, allowing users to analyze application performance through natural language queries. Key capabilities include querying CPU performance and memory usage, exploring profiling metadata like profile types and labels, and providing AI-driven code optimization suggestions directly within development environments like Claude Code or Cursor.