"How to create Grafana dashboards" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
290+ quality-scored API capabilities for AI agents across 27 countries via MCP.
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/
Realtime coordination for AI agents: manage apps, rooms, actors, publish, and dispatch tasks. Visit https://nolag.app and setup your account.
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
Free anonymous website, DNS, email and TLS checks, plus read-only access to your monitors.
Real-time status & uptime monitoring for 200+ popular APIs — is it down, and how reliable?
performance-review MCP — wraps StupidAPIs (requires X-API-Key)
Cloudflare Radar MCP — internet observatory (traffic, attacks, BGP, quality)
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
Manage Cronitor monitors and send telemetry pings — list, inspect, create, update, delete.
Read status-page status, services, incidents and metrics; create, update and publish incidents.
Manage incidents and on-call: list/create/update incidents, who is on call, on-call overrides.
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
Query Checkly synthetic monitoring — checks, statuses, results, alerts, reporting and dashboards.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
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.
