Calculator

Provides advanced mathematical capabilities including arithmetic, symbolic math, statistics, and matrix operations through an MCP client.
  • python

42

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "huhabla-calculator-mcp-server": {
      "command": "uvx",
      "args": [
        "--from",
        "calculator-mcp-server@git+https://github.com/huhabla/calculator-mcp-server.git",
        "--",
        "calculator-mcp-server",
        "--stdio"
      ]
    }
  }
}

You can use the Mathematical Calculator MCP Server to perform advanced mathematical tasks—from quick arithmetic to symbolic math, statistical analysis, and matrix operations—within your MCP-enabled environment. It’s designed to be accessed by an MCP client, enabling Claude to perform calculations, solve equations, derive expressions, compute integrals, analyze data, and manipulate matrices with ease.

How to use

You interact with the Calculator MCP Server through your MCP client. Start the server and connect it as a local or remote MCP endpoint, then invoke any of its capabilities by framing your queries as standard MCP requests. Use it to perform a wide range of tasks, such as evaluating expressions, solving equations, differentiating or integrating expressions, computing basic statistics, and executing matrix operations. For example, you can ask the server to evaluate a complex expression, solve a quadratic equation, compute the mean of a dataset, or multiply two matrices. The server exposes these capabilities as tools you can call from your MCP client.

How to install

Prerequisites you need to have before installing are Python 3.10 or newer, and a method to run Python packages (uv is recommended; pip also works). You should also have Claude Desktop installed to use the MCP server with Claude.

Install steps

# 1. Clone the calculator MCP server repository
git clone https://github.com/huhabla/calculator-mcp-server.git
cd calculator-mcp-server

# 2. Option 1: Use the provided setup script
chmod +x setup_venv.sh
./setup_venv.sh

# 3. Option 2: Manually set up the virtual environment
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

# 4. Run doctests to verify everything works
bash run_doctests.sh

Integration with Claude Desktop

To expose the Calculator MCP Server to Claude Desktop, configure the MCP server entry in Claude’s client settings. The following stdio configuration uses uvx to load the server directly from the Git URL and run it with the appropriate arguments.

{
  "mcpServers": {
    "calculator": {
      "name": "calculator",
      "type": "stdio",
      "command": "uvx",
      "args": [
        "--from",
        "calculator-mcp-server@git+https://github.com/huhabla/calculator-mcp-server.git",
        "--",
        "calculator-mcp-server",
        "--stdio"
      ]
    }
  }
}

Usage examples

Once connected, you can request a variety of mathematical operations. Examples include basic calculations, solving equations, derivatives, integrals, and statistical analyses, as well as matrix operations. Use concise natural-language prompts that specify the task you want to perform.

Development

For development and debugging, you can run the MCP server in development mode to test tools interactively.

License

This project is licensed under the MIT License.

Available tools

basic_calculation

Evaluate mathematical expressions safely and return results.

symbolic_solve

Solve equations (linear, quadratic, polynomial, etc.).

derivative

Compute derivatives of expressions with respect to a variable.

integral

Compute integrals of expressions.

mean

Calculate the mean of a dataset.

median

Calculate the median of a dataset.

mode

Calculate the mode of a dataset.

variance

Compute the variance of a dataset.

stddev

Compute the standard deviation of a dataset.

correlation

Compute the correlation coefficient between two datasets.

linear_regression

Perform linear regression on a set of points.

matrix_add

Add two matrices.

matrix_multiply

Multiply two matrices.

matrix_transpose

Transpose a matrix.

Built by
VeilStrat
AI signals for GTM teams
© 2026 VeilStrat. All rights reserved.All systems operational