math-mcp-learning-server

Educational MCP server with 17 tools, persistent workspace, and cloud hosting. Built with FastMCP and the official Model Context Protocol Python SDK.

Available on the MCP Registry (io.github.clouatre-labs/math-mcp-learning-server) and PyPI.

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

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.

Documentation

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