"Information Related to Servers" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
290+ quality-scored API capabilities for AI agents across 27 countries via MCP.
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/
Free anonymous website, DNS, email and TLS checks, plus monitor read and opt-in write access.
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Check updown.io uptime checks, downtimes, response metrics and status pages, and create checks.
Trace events to function runs to the failing step, and bulk-cancel runs.
Agent-native service discovery and purchase-intent routing to Stripe-hosted checkout.
Stateless MCP gateway and OTel span-streaming bridge for hosted MCP servers.
Observed facts on public MCP servers: protocol checks, tool changes, signed evidence. No verdicts.
Weekly scans of MCP servers for availability and consistency, with a public dashboard.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
Live status probes plus published uptime and incident history for 280+ APIs and cloud services.
MCP tool observatory: do registry servers answer, and are their answers true? No key.
Report-To group count, body discarded
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Vantaj uptime monitoring via MCP - manage monitors, heartbeats, incidents, and status pages.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
Enterprise AI Control Plane: governance, guardrails, spend tracking, compliance & smart routing.
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.
