"Unity Development Platform or Related Topics" matching MCP connectors:
Matching Connector Tools:
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
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.
Track AWS SES bounces, complaints, and delivery stats from your coding agent. Requires a Sessy API key from https://app.sessy.do/api_keys. Does not send email or change SES settings.
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
Free MCP tools: the only MCP linter, health checks, cost estimation, and trust evaluation.
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.
RUM platform for web performance analytics, Core Web Vitals, and third-party script monitoring.
Log, evaluate, and ground AI decisions against authority context. Returns PASS, WARN, or BLOCK.
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.