"Checking the current time" matching MCP connectors:

Real-time status for 75+ AI services (OpenAI, Anthropic, Cursor). No auth, CORS-enabled.

Proxy Gemini (Vertex AI) completions wrapped in OpenTelemetry trace spans; returns the answer plus t

Gain visibility into the performance, availability, and health of your apps and infrastructure.

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.

Real-time web analytics for AI agents: query traffic, funnels, revenue, and manage your sites.

High-performance array aggregation and metrics clearing engine. Cleans and bucket-groups noisy metric streams via an $O(N)$ single-pass data sweep. Operates natively with the pay-per-call x402 micropayment framework.

AI agent observability for production traces, natural-language insights, and improvement loops.

Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.

Track Keito time entries and LLM costs from AI agents.

Connect AI assistants to AppAmbit — the command center for your mobile & desktop apps. Query real-time analytics, sessions, and crash reports; read and push remote config; send push notifications, provision and query managed per-app SQLite databases, deploy serverless Cloud Code functions; and manage a headless CMS. Also generates SDK setup snippets and runs integration diagnostics. Supports .NET MAUI, Swift, Objective-C, Android and more. Built for indie devs, mobile teams, and agencies.

Free MCP tools: the only MCP linter, health checks, cost estimation, and trust evaluation.

Service level agreement monitoring for the Hive agent fleet

Real-time health monitoring and heartbeat tracking for agent services

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.

Interact with a global network measurement platform.Run network commands from any point in the world

Data + AI observability — monitor and troubleshoot production-grade agents and the context they use.

13 neural engines for time-series anomaly detection, classification, and root cause analysis.

Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.

The Polar Signals MCP server enables AI assistants to connect directly with performance profiling data, allowing users to analyze application performance through natural language queries. Key capabilities include querying CPU performance and memory usage, exploring profiling metadata like profile types and labels, and providing AI-driven code optimization suggestions directly within development environments like Claude Code or Cursor.