This MCP server provides a symbolic mathematics compute engine built on SymPy. It can perform basic arithmetic, algebraic manipulations (expand, factor, simplify), calculus (differentiation, integration, limits), solve equations (including systems), and matrix operations (inversion, eigenvalues/eigenvectors). You interact with the server by sending expressions or commands through the MCP protocol, and it returns computed results such as simplified expressions, numerical values, or symbolic forms. The included example usage shows typical operations like expanding polynomials, differentiating trigonometric expressions, solving equations, and computing matrix properties. Use the calculate_expression tool to pass an expression as a string; the server parses the string, executes the appropriate SymPy operations, and returns the result in a structured form.

Prerequisites:

• Python 3.8+ (or a compatible Python environment)
• Internet access to install dependencies
• Git (optional, for cloning the repository)

Local installation steps:

1. Clone the repository (or obtain the code): git clone https://github.com/611711Dark/mcp-calculate-server.git cd mcp-calculate-server

2. Create and activate a virtual environment: python -m venv venv

   macOS/Linux

   source venv/bin/activate

   Windows

   venv\Scripts\activate.bat

3. Install the package in editable mode (this pulls in dependencies like sympy): pip install -e .

4. Configuration (example): You can configure the MCP client to invoke this server using uv as shown below. Create a config snippet like: { "calculate_expression1": { "isActive": true, "command": "uv", "args": [ "run", "--directory", "/path/to/mcp_calculate_server", "server.py" ] } }

5. Run the server through the MCP framework using the configured entry (adjust paths as needed).

Optional Smithery installation (if you want to install via Smithery): npx -y @smithery/cli install @611711Dark/mcp_sympy_calculate_server --client claude

Prerequisites recap: ensure you have Python installed, a working virtual environment, and network access to install dependencies. Update paths in the configuration to reflect your local checkout location.

Notes and tips:

• The server relies on SymPy for symbolic math; ensure SymPy is installed (pip install sympy) when not using the editable install path.
• In the MCP config, point the directory argument to the actual location of the mcp_calculate_server checkout containing server.py.
• If you modify dependencies, re-run pip install -e . to pick up changes.
• For debugging, run server.py directly in a Python environment to check for import or path issues before wiring it through MCP.
• Ensure the Python environment used to run the MCP server has access to the virtual environment where the package is installed.
• The MCP protocol will return results in a structured format; handle exceptions such as undefined symbols or singular matrices by checking error messages from the response.