clouatre-labs/math-mcp-learning-server

v0.11.3 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

Published 3mo MCP Developer Tools

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✓ No known CVEs patched

Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

calculator educational fastmcp fastmcp-3 mathematics mcp

+3 more

mcp-server python tutorial

Summary

AI summary

Refactors introduce UUID‑based session tracking, Pydantic result models for calculations and visualizations, and remove dead code.

Full changelog

Refactors and Documentation

Refactors tool output to structured Pydantic models, replaces the session ID anti-pattern with UUID-based tracking, and adds architecture documentation with Mermaid diagrams and ADRs.

Installation

# Local (stdio transport)
uvx math-mcp-learning-server

# Remote (streamable HTTP, no install needed)
# https://math-mcp.fastmcp.app/mcp

What's Changed

Refactors

UUID-based session ID: Replace id(ctx.lifespan_context) memory-address anti-pattern with UUID via ctx.set_state (#227)
Pydantic result models (calculate, matrix, persistence): Replace manual content blobs with typed Pydantic models for proper MCP serialization (#233)
Pydantic result models (visualization): Replace manual content blobs with typed Pydantic models for chart tools (#235)
Dead code removal: Remove orphaned calculation_history tracking blocks after session ID migration (#229)
Progress reporting: Add ctx.report_progress to statistics tool for multi-stage feedback (#226)

Documentation

README refresh: Update for clarity and accuracy (#218)
Architecture docs: Add ARCHITECTURE.md with Mermaid component and flow diagrams (#224)
Architecture Decision Records: Add ADRs for key design decisions (#225)
README and CONTRIBUTING restructure: Fix stale references and improve organization (#238)

Full Changelog: https://github.com/clouatre-labs/math-mcp-learning-server/compare/v0.11.2...v0.11.3

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About clouatre-labs/math-mcp-learning-server

Educational MCP server for math operations, statistics, visualization, and persistent workspaces. Built with FastMCP 2.0.

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