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

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Enables Claude to translate natural-language business questions into safe, read-only SQL queries by exposing tools for listing tables, inspecting schemas, and executing row-capped SELECT statements against PostgreSQL.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

A secure database query service built on FastMCP framework that allows users to query MySQL databases using natural language, with comprehensive permission management and security controls.

Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data including querying, creating, updating, and deleting entities through SAP BTP integration.

Provides read-only tools to search and retrieve timestamped transcript evidence from the Pinkbike Podcast, enabling bike research questions to be answered with cited source passages.

Enables AI assistants to query hundreds of models across OpenAI, Google, and OpenRouter, with model discovery, deep-research jobs, and image generation.

A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.

Enables querying SINTEGRA TO (state tax information) through a read-only MCP server, using natural language.

An MCP server that connects to Telegram as your real user account and exposes read-only tools to read and search messages, list chats and folders, inspect group info, and download media.

Read-only MCP server for querying SEFAZ Tocantins (SEFAZ TO) NFC-e (electronic consumer invoice) data from official government sources via natural language, working with any MCP-compatible client such as Claude, Cursor, VS Code, and more.

Enables AI assistants to answer questions about the operator's current focus, engagements, reusable patterns, availability, and service offerings, with responses grounded in structured data and including confidence labels and source citations.

Enables users to search Samin Yasar's video library and receive full-video recommendations grounded in transcript evidence with links to exact matched caption cues.

Enables Claude Desktop to interact with PostgreSQL databases through natural language for schema exploration, data analysis, and query execution. Users can search schemas, describe tables, and perform read or write operations without needing to write manual SQL.