"A resource for finding 3D models" matching MCP servers:

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 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.

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.

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.

Zero-dependency charts for Python and AI agents. SVG and PNG, 15 chart types, a one-line MCP server, and a Claude skill.

Turn any CSV into a stunning interactive dashboard with one command — works as CLI, MCP server, or AI skill

A read-only, cross-platform visualization layer for Cortex that renders memory, sessions, and code into six live reading angles (graph galaxy, 3D anatomical brain, execution trace, consolidation board, knowledge browser, and wiki) without ever writing a memory.

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.

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.

MCP server that enables natural-language-driven, headless HEC-RAS modeling, letting agents inspect, edit, run, compare, and plot 1D/2D hydraulic models without the GUI.

Computes biorhythm values (physical, emotional, intellectual) and generates a PNG chart showing sine curves based on birth date and optional target date.

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

Enables assistants to read and analyze construction schedules like a scheduler: CPM, float, critical paths, DCMA 14-point, logic checks, update-to-update comparison, baseline variance, and S-curves from P6 XER and MS Project files.

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 (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.

Open-source dotted maps and animated 3D globes. Pick one of 21 looks for a country or the world, build share links, open and edit a pasted link, and get embed code. Hosted at https://globestudio.app/mcp or run with npx @globestudio/mcp. Free, MIT, no API key.

Enables natural-language interaction with Ladybug Tools for building performance simulation, 3D modeling, and data visualization, allowing agents to perform complex environmental analysis tasks without CAD software.

A production-grade MCP server for enterprise sales analytics, enabling LLM clients to query, analyze, and visualize sales data from a SQLite database through structured tools, resources, and prompts.

An unofficial MCP server for generating infographics and visuals from text using the Napkin AI API, enabling AI assistants to create professional diagrams, mindmaps, and charts.

Exposes NeuroGraph's scientific API to AI models as MCP tools, enabling them to query, analyze, and visualize brain networks — regions, tracts, connectivity, literature, and cross-species homologies — drawn from a portable SSD-based neuroimaging data library. Lets models read real atlas data, load datasets, compute graph metrics, and produce visualization scene descriptors without acting as the scientific engine itself.