math-mcp-learning-server

<!-- mcp-name: io.github.clouatre-labs/math-mcp-learning-server -->

<h1 align="center">math-mcp-learning-server</h1>

<p align="center"> <a href="https://pypi.org/project/math-mcp-learning-server/"><img alt="PyPI" src="https://img.shields.io/pypi/v/math-mcp-learning-server?style=for-the-badge&color=3b82f6" height="20"></a> <a href="https://pypi.org/project/math-mcp-learning-server/"><img alt="Python" src="https://img.shields.io/pypi/pyversions/math-mcp-learning-server?style=for-the-badge" height="20"></a> <a href="LICENSE"><img alt="License" src="https://img.shields.io/badge/license-Apache--2.0-blue.svg?style=for-the-badge" height="20"></a> <a href="https://api.reuse.software/info/github.com/clouatre-labs/math-mcp-learning-server"><img alt="REUSE" src="https://img.shields.io/reuse/compliance/github.com/clouatre-labs/math-mcp-learning-server?style=for-the-badge" height="20"></a> <a href="https://www.bestpractices.dev/projects/12334"><img alt="OpenSSF Best Practices" src="https://img.shields.io/cii/level/12334?style=for-the-badge" height="20"></a> </p>

<p align="center"><strong>Educational MCP server with 17 tools, persistent workspace, and cloud hosting.</strong> Built with <a href="https://gofastmcp.com">FastMCP</a> and the official <a href="https://github.com/modelcontextprotocol/python-sdk">Model Context Protocol Python SDK</a>.</p>

<p align="center"> Available on the <a href="https://registry.modelcontextprotocol.io/">MCP Registry</a> (<code>io.github.clouatre-labs/math-mcp-learning-server</code>) and <a href="https://pypi.org/project/math-mcp-learning-server/">PyPI</a>. </p>

Demo

See CONTRIBUTING.md for instructions to record your own demo.

Quick Start

Cloud (No Installation)

Connect your MCP client to the hosted server:

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "math-cloud": {
      "transport": "http",
      "url": "https://math-mcp.fastmcp.app/mcp"
    }
  }
}

Local Installation

{
  "mcpServers": {
    "math": {
      "command": "uvx",
      "args": ["math-mcp-learning-server[scientific,plotting]"]
    }
  }
}

For other installation options (basic, scientific-only, plotting-only), see CONTRIBUTING.md.

Tools

Category	Tool	Description
Workspace	workspace_save	Save calculations to persistent storage
	workspace_load	Retrieve previously saved calculations
Math	calc_expression	Safely evaluate mathematical expressions
	calc_statistics	Statistical analysis (mean, median, mode, std_dev, variance)
	calc_interest	Calculate compound interest for investments
	calc_units	Convert between units (length, weight, temperature)
Matrix	matrix_multiply	Multiply two matrices
	matrix_transpose	Transpose a matrix
	matrix_determinant	Calculate matrix determinant
	matrix_inverse	Calculate matrix inverse
	matrix_eigenvalues	Calculate eigenvalues
Visualization	plot_function	Plot mathematical functions
	plot_histogram	Create statistical histograms
	plot_line_chart	Create line charts
	plot_scatter	Create scatter plots
	plot_box_plot	Create box plots
	plot_financial_line	Create financial line charts

Resources

• math://workspace - Persistent calculation workspace summary
• math://history - Chronological calculation history
• math://functions - Available mathematical functions reference
• math://constants/{constant} - Mathematical constants (pi, e, golden_ratio, etc.)
• math://catalog/tools - Tool catalog with metadata and usage examples
• math://variables - Active variables in the current workspace
• math://test - Server health check

Prompts

• math_tutor - Structured tutoring prompts (configurable difficulty)
• formula_explainer - Formula explanation with step-by-step breakdowns

See Usage Examples for detailed examples.

Development

See CONTRIBUTING.md for development setup, testing, and contribution guidelines.

Security

• OpenSSF Best Practices Silver - Fewer than 1% of open source projects reach this level
• REUSE/SPDX - License compliance for all files
• Signed Commits - GPG-signed commits required
• Dependency Scanning - Automated updates via Renovate
• pip-audit CVE Scanning - Automated dependency vulnerability checks
• gitleaks Secret Scanning - Detects secrets in code and history
• zizmor GitHub Actions Security - Workflow security scanning
• commitlint Enforcement - Conventional commit validation in CI
• OpenSSF Scorecard - Continuous open source security assessment

<details> <summary><strong>calc_expression safety</strong></summary>

The calc_expression tool uses restricted eval() with a whitelist of allowed characters and functions, restricted global scope (only math module and abs), and no access to dangerous built-ins or imports. All tool inputs are validated with Pydantic models. File operations are restricted to the designated workspace directory. Complete type hints and validation are enforced for all operations.

</details>

Documentation

• Architecture
• Cloud Deployment Guide
• Usage Examples
• Contributing Guidelines
• Maintainer Guide
• Roadmap
• Code of Conduct
• License