"Using LLMs for Retrieving and Processing Web Content" matching MCP servers:

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

A Model Context Protocol server that enables AI to interact with GeoGebra for mathematical visualization, offering over 25 tools for geometry, functions, algebra, and more.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Provides aerodynamic analysis tools through MCP, enabling geometry generation, meshing, CFD solving, and visualization for 2D airfoils.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Enables your own ChatGPT to build and manage a collaborative work board—dashboards, categories, datasets, monitors, and policies—through typed WebMCP tools, with human approval, audit trails, and guardrails enforced on every action.

MCP server for Microsoft Power BI and Fabric, enabling Claude to discover workspaces, semantic models, generate and execute DAX queries, and retrieve report metadata via device-code authentication.

Enables AI assistants to drive a live TradingView chart in Chrome, turning natural-language trading ideas into compiled Pine Script indicators, adding them to charts, and reading back results. It also supports chart navigation, indicator management, screenshots, and strategy tester backtest results.

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

Enables AI assistants to control a logged-in TradingView chart in Chrome, including writing and compiling Pine Script indicators, adding them to charts, changing symbols and timeframes, capturing screenshots, and retrieving strategy tester results.

Gives Claude deep tool-level control over Microsoft Excel files (.xlsx, .xlsm, .csv, .tsv) with 164 tools across 24 modules for reading, writing, formatting, formulas, charts, data analysis, and more.

Options analytics an agent can drive: import a permitted chain, solve implied volatility, build a sixteen-Greek ladder, map dealer gamma walls, rank twenty-three structures, run a GARCH-t simulation with a convergence gate, and backtest with modelled premiums. Twelve stdio tools; every output is a schema-validated JSON file with source, assumptions and a degraded flag. Research only, no orders.

Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

Enables LLMs to discover, understand, and generate Teal R Shiny applications for clinical trial data analysis.

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.

Enables MCP-capable LLMs to generate and render ephemeral Prefab UI interfaces at runtime, with tools for generating UI code and searching Prefab components.

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

Enables LLMs to generate visual summary reports from CSV datasets using MCP Resources, Tools, and Prompts, without exposing raw data to the model.

Generates and downloads charts using QuickChart.io through Claude Desktop and other MCP clients.

Enables agents to validate climate-processing configurations, inspect sample CSV data, and run a deterministic pipeline that aggregates daily records into monthly summaries and plots, with sandboxed paths and isolated outputs.