"Desktop Automation Tools with Ultrawide Monitor Support (3840x1080p)" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
Monitor uptime and incidents, run checks, and publish status updates from your Uptimepage org.
Vouch — independently measured reliability scores for MCP tools, not self-reported claims.
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
Stateful WebSocket session registry with per-connection Shannon entropy delta tracking for schema di
Dead-man switch monitors for cron & AI agents with dependency-cascade alerts. No account needed.
Discover Frontier inference capabilities and read sanitized usage through read-only tools.
CVE intelligence: exploitation (KEV/EPSS), detection coverage, fixed versions. All tools keyless.
Monitoring for agencies — uptime, SSL, DNS, blocklists, AI visibility, MCP health. 8 no-auth tools.
186 real AI agent post-mortems, 107 of them measurement failures. Free tools, paid via x402.
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
Diagnose AI workflows for failure, security, and handoff risks — RED/AMBER/GREEN per node.
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
AI-ready vendor incident status with public active incidents and plan-scoped history.
Cloudflare Workers MCP server: cron-monitor
Ecosystem monitoring: service status and x402 activity metrics
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.
