"Systems or platforms that support dynamic registration" matching MCP connectors:

Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?

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

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

Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.

Uptime, SSL, domain, and Core Web Vitals monitoring for websites and APIs. List, create, update, and pause monitors; read incident history with AI-generated diagnosis; pull Lighthouse and CrUX page speed data. OAuth 2.0 with dynamic client registration — works out of the box with Claude Desktop connectors. Free plan: 20 monitors, read-only MCP.

AI visibility across 8 LLM platforms. 30 tools, most need no API key. EU-hosted, free.

Log, evaluate, and ground AI decisions against authority context. Returns PASS, WARN, or BLOCK.

API and website monitoring that validates the JSON a response returns, not just its status code. Create endpoint checks, pull incident reports carrying the actual failed payload, and read health scores from your editor.

Open-source agent that observes and fixes your application. Query logs, traces, metrics, incidents.

Uptime, SSL, DNS and domain monitoring you can talk to from Claude or any MCP client.

Mobile observability for AI agents. Investigate crashes, hangs, ANRs, bugs, and app performance, and triage app store reviews, directly from your IDE or terminal.

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.

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.

Cloud hosted Okahu MCP server that helps you manage genAI trace data