"A query about tasks" matching MCP connectors:

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/

Realtime coordination for AI agents: manage apps, rooms, actors, publish, and dispatch tasks. Visit https://nolag.app and setup your account.

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.

Query analyzed WebRTC sessions: observations, deductions, experience scores, and AI summaries.

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

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

Query Checkly synthetic monitoring — checks, statuses, results, alerts, reporting and dashboards.

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

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

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

Real-time web analytics for AI agents: query traffic, funnels, revenue, and manage your sites.

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

Monitor websites, APIs, and servers: create monitors, triage incidents, and query uptime stats.

Set up uptime monitoring from your editor: create checks, configure alerts, query uptime history.