mathematica-mcp-full 0.7.6

Full GUI control of Mathematica notebooks and kernel via Model Context Protocol

Mathematica MCP

Give your AI Agent the power of Wolfram Language.

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Who This Is For

Audience	Use Case
Researchers using LLM coding assistants	Run Mathematica from Claude/Cursor/VS Code without leaving your editor
Data scientists	Import, transform, and visualize data through natural language
Educators	Create interactive Mathematica notebooks through AI conversation
Not for	Production web services, untrusted multi-tenant environments

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What is this?

An MCP Server that gives AI agents a direct interface to your local Wolfram Engine. 79 tools across configurable profiles for symbolic reasoning, visualization, and notebook control.

Watch it in action

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Quick Start

Prerequisites

Before installing, you need:

1. Mathematica 14.0+ with wolframscript in your PATH

   • Download Mathematica
   • macOS: Add to ~/.zshrc: export PATH="/Applications/Mathematica.app/Contents/MacOS:$PATH"

2. uv package manager

   curl -LsSf https://astral.sh/uv/install.sh | sh
   

One-Command Setup (Recommended)

# For Claude Desktop
uvx mathematica-mcp-full setup claude-desktop

# For Cursor
uvx mathematica-mcp-full setup cursor

# For VS Code (requires GitHub Copilot Chat extension)
uvx mathematica-mcp-full setup vscode

# For OpenAI Codex CLI
uvx mathematica-mcp-full setup codex

# For Google Gemini CLI
uvx mathematica-mcp-full setup gemini

# For Claude Code CLI
uvx mathematica-mcp-full setup claude-code

# Optional: select a tool profile (default is "full")
uvx mathematica-mcp-full setup claude-desktop --profile notebook

Then restart Mathematica and your editor. Done!

VS Code: Alternative setup via Command Palette

Prerequisite: GitHub Copilot Chat extension must be installed - MCP support is built into Copilot.

1. Press Cmd+Shift+P (Mac) / Ctrl+Shift+P (Windows)
2. Type "MCP" → Select "MCP: Add Server"
3. Choose "Command (stdio)" — not "pip"
4. Enter command: uvx
5. Enter args: mathematica-mcp-full
6. Name it: mathematica
7. Choose scope: Workspace or User

Alternative: Interactive Installer

bash <(curl -sSL https://raw.githubusercontent.com/AbhiRawat4841/mathematica-mcp/main/install.sh)

Verify Installation

uvx mathematica-mcp-full doctor

Tip: If you encounter errors after updating, clear the cache:

uv cache clean mathematica-mcp-full && uvx mathematica-mcp-full setup <client>

Tool Profiles

Choose how many tools to expose: math (~25 tools), notebook (~44), or full (~79, default). Pass --profile during setup or set MATHEMATICA_PROFILE env var. See the Technical Reference for details.

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Manual Installation

Click to expand manual setup instructions

1. Clone & Install:

   git clone https://github.com/AbhiRawat4841/mathematica-mcp.git
   cd mathematica-mcp
   uv sync
   

2. Install Mathematica Addon:

   wolframscript -file addon/install.wl
   

   Restart Mathematica after this step.

3. Configure your editor (replace path with your actual path):

   Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

   {
     "mcpServers": {
       "mathematica": {
         "command": "uv",
         "args": ["--directory", "/path/to/mathematica-mcp", "run", "mathematica-mcp-full"]
       }
     }
   }
   

   Cursor (~/.cursor/mcp.json):

   {
     "mcpServers": {
       "mathematica": {
         "command": "uv",
         "args": ["--directory", "/path/to/mathematica-mcp", "run", "mathematica-mcp-full"]
       }
     }
   }
   

   VS Code (~/.vscode/mcp.json):

   Note: VS Code MCP requires GitHub Copilot Chat extension.

   {
     "servers": {
       "mathematica": {
         "type": "stdio",
         "command": "uv",
         "args": ["--directory", "/path/to/mathematica-mcp", "run", "mathematica-mcp-full"]
       }
     }
   }
   

📖 See the Installation Guide for troubleshooting and advanced setup.

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What You Can Do

1. Solve and Verify a Calculus Problem

"Integrate x^2 sin(x) from 0 to pi, then verify by differentiating."

Agent calls: execute_code("Integrate[x^2 Sin[x], {x, 0, Pi}]")
=> -4 + Pi^2

Agent calls: verify_derivation(
  steps=["Integrate[x^2 Sin[x], {x, 0, Pi}]", "-4 + Pi^2"]
)
=> {"success": true, "report": "Step 1 → 2: ✓ VALID\n...\n**Summary**: All steps are valid!", "raw_data": {...}, "format": "text"}

2. Generate a 3D Plot

"Plot the sombrero function and export it."

Agent calls: execute_code("Plot3D[Sinc[Sqrt[x^2 + y^2]], {x, -4, 4}, {y, -4, 4}]")
=> [3D surface plot rendered as image]

Agent calls: export_graphics("Plot3D[Sinc[Sqrt[x^2+y^2]], {x,-4,4}, {y,-4,4}]", "/tmp/sombrero.png", "PNG")

3. Read and Analyze a Notebook

"Show me the outline of SinPlot.nb, then extract the code cells."

Agent calls: read_notebook("SinPlot.nb", output_format="outline")
=> {"success": true, "format": "outline", "section_count": 0, "sections": []}

Agent calls: read_notebook("SinPlot.nb", output_format="json")
=> {"success": true, "cell_count": 2, "code_cells": 1, "cells": [{"style": "Input", "content": "Plot[Sin[x], {x, 0, 2 Pi}]"}, ...]}

Beyond these workflows: symbolic computation, 2D/3D visualization, notebook operations, Wolfram Alpha queries, data import/export (250+ formats), and debugging tools. See the Technical Reference for the full tool list.

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Documentation

• Technical Reference — Architecture, tools, and configuration
• Security Model — Threat model, permissions, and vulnerability reporting
• Benchmarks — Performance data and reproduction steps
• Contributing — Development setup, testing, and PR process
• Changelog — Version history
• Examples — Polished agent session walkthroughs

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License

MIT License