"How to automate uploads on Douyin (TikTok China)" matching MCP connectors:
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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/
Real-time status & uptime monitoring for 294 popular APIs — is it down, and how reliable?
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.
Observatory operated and funded by devlo: real tools on frozen tasks; intervals, cost, limits.
Cookieless web analytics your coding agent reads: traffic answers, deploy impact, what broke. One connection covers every site on the account.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
Report-To group count, body discarded
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.
Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Read incidents, services, teams, on-call schedules; acknowledge, resolve and note incidents.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
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.
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
