"Collaborative Communication Between AI Systems" matching MCP connectors:

290+ quality-scored API capabilities for AI agents across 27 countries via MCP.

Zero-trust gateway for AI agents: score tool calls, verify agent cards, enforce policy, audit.

Read-only triage for n8n, MCP, webhook, and AI agent workflow production failures.

Proxy Gemini (Vertex AI) completions wrapped in OpenTelemetry trace spans; returns the answer plus t

AI compute infrastructure intelligence: facilities, supply chains, sovereign AI, export controls.

Real-time status for 75+ AI services (OpenAI, Anthropic, Cursor). No auth, CORS-enabled.

Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.

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

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

Public MCP digital twin with synthetic systems and an agent firewall. No customer data.

Read-only Increase banking observability plus one safe non-money-moving write, for AI agents.

Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.

Diagnose AI workflows for failure, security, and handoff risks — RED/AMBER/GREEN per node.

Enterprise AI Control Plane: governance, guardrails, spend tracking, compliance & smart routing.

Live reliability for AI agent tools: is it working right now, and how do I call it correctly?

AI-ready vendor incident status with public active incidents and plan-scoped history.

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.

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.

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