"Using PostgreSQL with n8n Workflow Automation" matching MCP connectors:
Matching Connector Tools:
Stateful WebSocket session registry with per-connection Shannon entropy delta tracking for schema di
Read-only triage for n8n, MCP, webhook, and AI agent workflow production failures.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
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.
Connect engineering metrics, DORA performance, and deploy risk scoring to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.
DORA OS Conductor — 16-tool meta-orchestrator for DORA compliance workflow automation.
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
Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.
Hosted MCP server for PostgreSQL diagnostics: slow queries, missing indexes, connection pressure.
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.
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Monitor, troubleshoot, and optimize your technology stack with Intelligent Observability.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
Know when your n8n workflows, URLs, and AI apps break, before your customers do.
Interact with a global network measurement platform.Run network commands from any point in the world
AI agent run monitoring with incident replay and SLA receipts.
Debug production issues using Shipbook logs and Loglytics error insights.