"A server for full math MCP" matching MCP servers:

A Python-based MCP server providing mathematical computation tools and plotting utilities for a wide range of math topics including calculus, matrix operations, statistics, and more.

Exposes a broad mathematics toolkit including symbolic algebra, calculus, numerical methods, linear algebra, statistics, discrete math, graph theory, rendering, and optional GPU acceleration via MCP tools for use with Claude Desktop and other MCP hosts.

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.

An MCP server that provides interactive 2D/3D math plotting, embedded CircuitJS circuit demonstrations, and locally rendered Manim slide videos for ChatGPT/Codex.

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

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.

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.

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

AI-powered Fantasy Premier League assistant — scored captain picks, transfer suggestions, differentials, fixture outlook, price predictions, live points, and a full manager hub that auto-detects your squad, bank balance, and free transfers.

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

Provides powerful symbolic mathematics and statistical analysis capabilities, enabling users to solve equations, compute derivatives and integrals, perform statistical tests, and analyze data through natural language requests.

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.

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 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.

Gives terminal coding agents a local browser canvas for rendering charts, tables, metrics, markdown, live widgets and sandboxed MCP App UIs that would otherwise reach them as raw JSON. Lets agents pose blocking visual multiple-choice questions and read back the user's clicks, selections and an animated architecture map of file activity.

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.