"A managed cloud provider that deploys my application" 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/

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.

Uptime watchdog and dead man switch for AI agents and cron jobs. Alerts you when a job goes silent.

Check real-time uptime and incident status for 285 APIs and cloud services.

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

Live status and health checks for AI coding providers: Claude, Cursor, Copilot, Codex and more.

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.

Read-only cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude

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

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

Build and monitor LLM apps on Orq.ai: AI gateway, agents, prompts, evals, traces.

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

Manage Kubernetes clusters, deployments, databases, secrets and observability on Mengi Cloud.

Draw your app's architecture on a live canvas and flag the bottlenecks and security gaps.

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.

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

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

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.

Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.