"A browser focused on stealth or privacy features" 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.

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

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.

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

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.

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

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.

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

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.

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