"A guide to finding people on LinkedIn by their name" 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/
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
MCP tool observatory: do registry servers answer, and are their answers true? No key.
A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
Free anonymous website, DNS, email and TLS checks, plus read-only access to your monitors.
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.
Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.
Read incidents, services, teams, on-call schedules; acknowledge, resolve and note incidents.
Manage incidents and on-call: list/create/update incidents, who is on call, on-call overrides.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve 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.
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.
