clouatre-labs/math-mcp-learning-server
🐍 ☁️ 🏠 🍎 🪟 🐧 - Educational MCP server for math operations, statistics, visualization, and persistent workspaces. Built with FastMCP 2.0.
Quick Install
{
"mcpServers": {
"clouatre-labs-math-mcp-learning-server": {
"command": "npx",
"args": [
"-y",
"clouatre-labs-math-mcp-learning-server"
]
}
}
}Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.
Documentation Overview
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 summarymath://history- Chronological calculation historymath://functions- Available mathematical functions referencemath://constants/{constant}- Mathematical constants (pi, e, golden_ratio, etc.)math://catalog/tools- Tool catalog with metadata and usage examplesmath://variables- Active variables in the current workspacemath://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.