"How to find people on LinkedIn by 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/
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?
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.
Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.
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.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
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.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
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.
