"Performing Email-Related Operations in Python" matching MCP connectors:
Matching Connector Tools:
Proxy Gemini (Vertex AI) completions wrapped in OpenTelemetry trace spans; returns the answer plus t
Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.
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
Governance and grounding layer for engineering teams running AI coding agents (Claude Code, Cursor, Codex). Grounds agents in your codebase's knowledge graph, and adds session audit, policy controls and cost/token visibility.
Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.
AI access to Hitsteps analytics, live visitors, uptime, goals, alerts, and chats.
Check infrastructure health, manage incidents, and run runbooks in Faultline.
Read-only Yandex Metrika MCP. Query visits, sources, geo, devices and more in plain language.
Register every AI agent, log every action, prove it. EU AI Act compliance built in.
MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.
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.
Interact with a global network measurement platform.Run network commands from any point in the world
Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.