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

Enables an agent to turn a paper's draft into editable Figma frames for publication-ready figures, checking every number against the paper and verifying the exported PDF.

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

Enables LLM clients to load, clean, visualize, and analyze tabular datasets, and to generate multi-format analytic reports through natural language instructions.

An HTTP MCP server for exploring CSV files that masks PII before any code execution, enabling safe data analysis with local or cloud LLMs.

A local, fully vectorized computational engine for stock market analysis that enables AI to perform factor calculation, strategy backtesting, IC analysis, and GPU-based multi-dimensional visualization using local DuckDB data.

A Model Context Protocol server for managing and analyzing investment portfolios. It enables users to create and update portfolios, fetch real-time stock data and news, generate performance reports, and receive investment recommendations through natural language.

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

Enables users to ask questions about self-hosted or Cloud Umami Analytics through a secure, model-friendly Model Context Protocol interface, with read-only tools for traffic, conversions, revenue, sessions, events, reports, and performance investigations.

Exposes semiconductor wafer analysis tools including wafer maps, P-charts, and statistical plots, enabling AI assistants to visualize and analyze wafer test data.

MCP server providing data analytics tools for AI agents to load, clean, analyze data, generate charts and dashboards.

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

Enables agents to turn structured data into production-ready static maps, returning rendered PNG and SVG URLs along with an editable map link.

Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.

Enables querying Tableau lineage through the Metadata API via MCP, supporting impact analysis, where-used lookups, and content search. Provides read-only tools for answering natural-language questions about workbooks, datasources, fields, and dependencies.

A demo MCP server that returns an interactive dashboard (bar chart with dataset selector) as an MCP App via the official MCP Apps extension (SEP-1865).

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.

Enables exploratory data analysis through an MCP server, allowing AI assistants to load datasets, compute summary statistics, generate diagnostic plots, perform correlation analysis, and produce full markdown reports.

An MCP server that extracts energy-usage charts from utility-bill PDFs, returning structured time-series data and annotated images.

Renders OHLCV data as candlestick chart PNGs and returns inline images. It is a pure renderer with no network access, allowing models to view charts generated from provided data.