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Math MCP Learning

Official registry Productivity

Educational MCP server with 17 math/stats tools, visualizations, and persistent workspace

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http math-mcp-learning 'https://math-mcp.fastmcp.app/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "math-mcp-learning": {
            "type": "http",
            "url": "https://math-mcp.fastmcp.app/mcp"
        }
    }
}
PYPI package math-mcp-learning-server
Claude Code 
claude mcp add math-mcp-learning -- uvx math-mcp-learning-server==0.12.5
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "math-mcp-learning": {
            "command": "uvx",
            "args": [
                "math-mcp-learning-server==0.12.5"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. math-mcp-learning-server
  2. Demo
  3. Quick Start
  4. Tools
  5. Resources
  6. Prompts
  7. Development
  8. Security
  9. Documentation

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

CategoryToolDescription
Workspaceworkspace_saveSave calculations to persistent storage
workspace_loadRetrieve previously saved calculations
Mathcalc_expressionSafely evaluate mathematical expressions
calc_statisticsStatistical analysis (mean, median, mode, std_dev, variance)
calc_interestCalculate compound interest for investments
calc_unitsConvert between units (length, weight, temperature)
Matrixmatrix_multiplyMultiply two matrices
matrix_transposeTranspose a matrix
matrix_determinantCalculate matrix determinant
matrix_inverseCalculate matrix inverse
matrix_eigenvaluesCalculate eigenvalues
Visualizationplot_functionPlot mathematical functions
plot_histogramCreate statistical histograms
plot_line_chartCreate line charts
plot_scatterCreate scatter plots
plot_box_plotCreate box plots
plot_financial_lineCreate 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

Frequently asked questions

What is Math MCP Learning?

Educational MCP server with 17 math/stats tools, visualizations, and persistent workspace

How do I install Math MCP Learning?

It runs as a remote server. In Claude Code: claude mcp add --transport http math-mcp-learning 'https://math-mcp.fastmcp.app/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Math MCP Learning need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Math MCP Learning open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains Math MCP Learning?

It is published by clouatre-labs. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.