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math-mcp-learning-server

PyPI Python License REUSE OpenSSF Best Practices

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

math-mcp 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
calc_expression safety

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

Release files for math-mcp-learning-server 0.12.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for math-mcp-learning-server 0.12.5
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math_mcp_learning_server-0.12.5-py3-none-any.whl Python 3 none any Details

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