"How to allow an LLM to ask questions to a user" matching MCP servers:

MCP Server for notify to telegram / weixin

Independent latency and uptime data for 46 hosted AI inference APIs, probed every 5 minutes from 4 regions with no gateway, plus a verified model deprecation calendar and Claude Code / Codex speed and accuracy drift. Four read-only tools, no API key; data CC BY 4.0.

Enables agents to check remaining Anthropic and OpenAI rate-limit quotas with reset times, plus Hermes Agent token usage, so bots can throttle or stop before hitting limits.

LLM cost optimization and provider usage visibility for MCP-capable agents.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

A scheduled MCP server that monitors Auth0 users by periodically collecting summaries, detecting suspicious admins, and auto-blocking them; it provides instant reports via SQLite and exposes tools for on-demand collection and configuration.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

MCP server for Tessera's LLM cost-optimization layer. Anchored spend, drift detection, recommendations as typed tools.

An MCP server that functions as an intelligent gateway for multiple LLM backends including OpenAI, Claude, and Ollama. It supports automatic provider fallback, streaming responses via Server-Sent Events, and real-time monitoring for robust AI integration.

Enables monitoring Auth0 users by collecting summaries, storing reports in SQLite, and auto-blocking suspicious admins, all through MCP tools without an LLM.

MCP server that wraps Nightjar's analytics API, enabling Claude Code to query events, funnels, dashboards, and metrics through natural language.

Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Enables LLM clients to ask natural-language questions about nodes in a FABRIC slice, returning grounded answers from the Node Exporter Full dashboard's fixed PromQL queries.

MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.

Enables LLM agents to monitor Mac thermals and control fan speed with safety limits enforced by a root daemon.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

Lets an AI assistant answer performance questions from Tideways data by reading projects, metrics, issues and traces through the read-only REST API.

Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.

An MCP server that wraps the taegis-magic CLI to allow AI assistants to query Secureworks Taegis XDR for alerts, events, investigations, threat intelligence, and tenants via natural language.