"A guide to finding NFL pre-game details" matching MCP servers:

A display-layer MCP server that renders text-game state — stats, inventory, locations, characters, dice results, and choices — as stable, themed cards in ChatGPT or Claude chats. It offers five visual skins and clickable option buttons that send the chosen action as the user's message, while leaving all rules and narrative to the AI.

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

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 plain-English analysis of game telemetry through tools for schema inspection, SQL queries, metric/KPI retrieval, anomaly sweeps, and synthetic data loading.

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.

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

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.

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.

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.

A Model Context Protocol server that renders Apache ECharts options to SVG, enabling AI agents to generate deterministic charts server-side without a browser.

A Model Context Protocol server for interacting with Lightdash, enabling AI assistants to discover data, create charts, and manage dashboards programmatically.

Enables AI clients to query live Minecraft recipe data and compute recipe trees, production plans, and searches from a running game or disk snapshots, with markdown, TSV, JSON, and HTML outputs.

Visualizes conversations as structured hierarchical mind maps by injecting a prompt that instructs the LLM to generate a JSON mind map — no external APIs required.

A Model Context Protocol server that provides a dynamic map interface with tools to add raster/vector layers, control map view, and modify paint properties.

Enables to interact with Felt maps programmatically through an MCP server. Supports listing, retrieving details, and creating maps with natural language.

Enables Magic: The Gathering players to analyze deck lists using real Scryfall oracle text, detecting synergies and conflicts. Generates three viewable documents: an interactive synergy map, a detailed guide, and a printable cheat sheet.

A review-only MCP server that provides tools for reviewing trade records against a live TradingView Desktop chart over Chrome DevTools Protocol on localhost.

Enables AI agents to drive TradingView Desktop, switch through a layout's symbols, and export each chart's rendered image, CSV data, and indicator details to local files, which they can then read in part or crop on demand. It runs jobs in a background process that does not consume agent tokens and keeps only the current day's output, leaving symbol choice, analysis, and use of the data to the caller.

An MCP server for Satisfactory that plans factories using your actual save files, reads game data, and runs LP/MILP optimization. It provides tools for game data lookup, factory planning, hard drive advice, and a local web map of your world.

Enables AI clients to generate over 26 chart types via MCP, automatically starting a private rendering service.