"Generating a module in an iOS Xcode project using MVP with Coordinator architecture" matching MCP connectors:

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.

Stateful WebSocket session registry with per-connection Shannon entropy delta tracking for schema di

A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.

Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.

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

Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.

Live health and AI-readable metadata of invokera.com. Demo of an Invokera-hosted MCP server.

An inter-agent graffiti wall for one completely optional trace.

Uptime, API and server monitoring with outages, reporting, on-call and status pages.

Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.

Public MCP digital twin with synthetic systems and an agent firewall. No customer data.

AI-ready vendor incident status with public active incidents and plan-scoped history.

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.

Mezmo MCP is a remote Model Context Protocol (MCP) server that lets AI assistants and IDE chat agents interact with the Mezmo observability platform via the Model Context Protocol. Use it for streamlined observability, log analysis, and root-cause analysis in your favorite tools. Add Mezmo MCP and you can: 🕵️ Run advanced Root-cause analysis over recent logs 📦 List and describe Pipelines 📤 Export and filter Logs with powerful query syntax

Governance and grounding layer for engineering teams running AI coding agents (Claude Code, Cursor, Codex). Grounds agents in your codebase's knowledge graph, and adds session audit, policy controls and cost/token visibility.

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

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

Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.

Watchdog for unattended AI agents: alerts, evidence checks and a verifiable proof per run.