"Allow WAR File Commands on Cisco OS" matching MCP connectors:

Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.

Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.

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

Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.

Read incidents, services, teams, on-call schedules; acknowledge, resolve and note incidents.

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

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.

DORA OS EventFabric - 14-tool event stream for DORA compliance signals and pub/sub fabric.

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

AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.

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

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

Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.

Manage incidents and on-call: list/create/update incidents, who is on call, on-call overrides.

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.

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

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.