"Finding people on LinkedIn by name" matching MCP connectors:

Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.

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 cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude

heera.it via Agentimus: AI readiness, traffic, request log, search & index reports, by approval.

Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith

AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.

EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.

Build and monitor LLM apps on Orq.ai: AI gateway, agents, prompts, evals, traces.

Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.

Manage Kubernetes clusters, deployments, databases, secrets and observability on Mengi Cloud.

Draw your app's architecture on a live canvas and flag the bottlenecks and security gaps.

MCP-native AI SRE. Exposes your production OpenTelemetry problems, traces, and logs over the Model Context Protocol, plus an AI remediation loop that opens a reviewed GitHub fix PR and verifies in production (reopening on regression). Tools include list_problems, get_problem, query_traces, detect_anomalies, and request_problem_remediation. Human-in-the-loop by default — the merge button stays yours.

Monitoring + status pages set up by talking to Claude. Auto-detects 30+ SDKs and your URLs.