"Information about pages or the term 'page'" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Is GitHub, npm, Cloudflare or your AI provider down right now? 20 status pages, one call.
Analytics for MCP servers. Find out which of your tools agents get wrong. MCPulse shows you which tools AI agents retry, which come back empty, and which they never call at all. Two lines inside your own server. It never sees your arguments or your results. getmcpulse.com
Free-trial AI fleet spend meter. Quote agent fleet spend from token usage. 100 calls or 14 days. No auth. Official MCP Registry: io.github.mtardy90-sudo/bootlace-ai-spendmap.
Fixter's MCP provides a stream-lined agentic way to onboard, setup and use the Fixter monitoring and observability platform. Check out more at https://fixter.dev/
Monitoring for the agent economy — liveness, latency, trust scoring for MCP endpoints
Cookieless web analytics your coding agent reads: traffic answers, deploy impact, what broke. One connection covers every site on the account.
Free uptime monitoring: HTTP/TCP/TLS/DNS + MCP server checks, cron heartbeats, status pages, alerts.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.
Manage status pages: components, incidents and maintenances; set live component status.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Read status-page status, services, incidents and metrics; create, update and publish incidents.
Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.
Vantaj uptime monitoring via MCP - manage monitors, heartbeats, incidents, and status pages.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Gain visibility into the performance, availability, and health of your apps and infrastructure.
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.
