"Campaign Monitor" 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.
Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.
Free anonymous website, DNS, email and TLS checks, plus monitor read and opt-in write access.
Know when cron jobs and AI agents stop running: create monitors and check in from your agent.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
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.
Cloudflare Workers MCP server: llm-output-quality-monitor
Service level agreement monitoring for the Hive agent fleet
- Ionhour MCPOAuth unavailablecom.ionhour.api
Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.
Monitor cron jobs and recurring work through a project-scoped Watchgoose connection.
Build and monitor LLM apps on Orq.ai: AI gateway, agents, prompts, evals, traces.
Monitor websites, APIs, and servers: create monitors, triage incidents, and query uptime stats.
Monitor, troubleshoot, and optimize your technology stack with Intelligent Observability.
Agent-native uptime monitoring. Create, inspect, and assert monitor health. Free 50-monitor tier.
Data + AI observability — monitor and troubleshoot production-grade agents and the context they use.
AI agent run monitoring with incident replay and SLA receipts.
