"A guide to finding articles on Medium" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
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/
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
Cookieless web analytics your coding agent reads: traffic answers, deploy impact, what broke. One connection covers every site on the 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.
Watchdog for unattended AI agents: alerts, evidence checks and a verifiable proof per run.
A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Manage incidents and on-call: list/create/update incidents, who is on call, on-call overrides.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
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.
