math-mcp-learning-server and sympy-mcp
These are complements: the educational server provides practical computation and visualization across multiple domains, while the symbolic manipulation tool offers deeper algebraic reasoning that could enhance the learning server's mathematical capabilities when integrated together.
About math-mcp-learning-server
clouatre-labs/math-mcp-learning-server
Educational MCP server with math operations, matrix algebra, data visualization, and persistent workspace using FastMCP 3.0
Implements 17 specialized tools spanning statistics, financial calculations, linear algebra, and chart generation, with sandboxed expression evaluation using restricted `eval()` and whitelist validation. Supports both cloud deployment via HTTP transport and local installation through uvx, with optional scientific (NumPy/SciPy) and plotting (Matplotlib) dependencies. Exposes resources for workspace state, calculation history, and mathematical constants, plus tutoring prompts for structured learning workflows.
About sympy-mcp
sdiehl/sympy-mcp
A MCP server for symbolic manipulation of mathematical expressions
Exposes 30+ SymPy tools via MCP including ODE/PDE solvers, tensor calculus for general relativity (Ricci, Einstein, Weyl tensors), vector calculus operators, and algebraic equation solving—enabling LLMs to delegate symbolic computation to a reliable backend rather than hallucinating mathematics. Implements stateful variable and expression management with configurable assumptions (real, complex, positive, etc.), allowing multi-step symbolic workflows where intermediate results persist across tool calls. Integrates with Claude Desktop, Cursor, and VS Code via stdio transport, with optional EinsteinPy dependency for relativistic spacetime metrics.
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