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

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    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.
    6
    MIT
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    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.
    4
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    Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.
    10
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    MIT
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    An MCP server that provides offline searchable Microsoft 365 roadmap data and live Azure status, enabling AI agents to answer questions about upcoming features, roadmap changes, and Azure incidents.
    4
    MIT
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    Enables AI agents to push and read metrics from EzStat, track counters/gauges, and ask natural-language questions about telemetry.
    4
    MIT
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    An MCP server that gives Claude read access to Umami web analytics, allowing natural language queries for stats, breakdowns, pageview trends, live visitors, and user journeys.
    10
    1
    MIT
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    Live .NET runtime diagnostics for AI assistants. Ask Claude to diagnose memory leaks, GC pressure, LOH fragmentation, and thread starvation in any running .NET process — no code changes required.
    7
    2
    MIT
  • F
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    A Model Context Protocol server that gives LLM clients full access to your AppDynamics monitoring data — plus the ability to create and manage dashboards and health rules.
    30
    5
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    Enables LLMs to answer Berserk observability questions by calling verified KQL tools instead of hand-authoring queries, with role-based tool filtering and automated query discovery.
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    1
    MIT
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    MCP server that wraps Cursor Enterprise API to enable AI agents to answer questions about team spending, usage, and model adoption.
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    2
    MIT
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    Сonnects to live JVMs via JDWP protocol, enabling LLM agents to autonomously debug Java applications — attach to a running process, pause threads, set breakpoints (including conditional), inspect stacks with auto-resolved object fields, evaluate methods, set variable values, and diagnose issues like deadlocks and hung queries.
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    MIT
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    Enables AI-powered analytics for OpenReplay user sessions through natural language queries. Supports session search, user journey analysis, error tracking, performance metrics, and funnel analysis to understand user behavior patterns.
    11
    2
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    Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.
    4
    1
    MIT
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    Exposes Okta incident-support and administrative workflows to MCP-compatible clients, enabling user investigation, group management, and system log queries.
    24
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    Apache 2.0