NumPy
About
Provides NumPy-based mathematical operations and statistical analysis tools for advanced numerical computations, data analysis, and linear algebra operations in Python environments.
Details
- Author
- colesmcintosh
- Repository
- colesmcintosh/numpy-mcp
- GitHub stars
- 1
- Downloads
- 227
- Categories
- Design, Developer Tools, AI, Infrastructure, Frontend, Other
Jump to
- Basic arithmetic operations (addition)
- Linear algebra computations (matrix multiplication, eigendecomposition)
- Statistical analysis (mean, median, standard deviation, min, max)
- Polynomial fitting
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
NumPyCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
The fastest way to get started is to install this server directly in Claude Desktop:
mcp install server.py --name "NumPy Calculator"
This project uses UV for dependency management. To install:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv
source .venv/bin/activate # On Unix/macOS
add
Add two integers together. Parameters: a (int), b (int)
matrix_multiply
Multiply two matrices. Parameters: matrix_a (List[List[float]]), matrix_b (List[List[float]])
eigen_decomposition
Compute eigenvalues and eigenvectors of a square matrix. Parameters: matrix (List[List[float]])
statistical_analysis
Calculate basic statistics for a dataset including mean, median, standard deviation, minimum value, and maximum value. Parameters: data (List[float])
polynomial_fit
Fit a polynomial of specified degree to the given data points. Parameters: x (List[float]), y (List[float]), degree (int, optional, default=2)
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"numpy": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}NumPy MCP Server
<div align="center">
<strong>A Model Context Protocol (MCP) server for numerical computations with NumPy</strong>
[![MIT licensed][mit-badge]][mit-url]
</div>
[mit-badge]: https://img.shields.io/badge/license-MIT-blue.svg
[mit-url]: ./LICENSE
[python-badge]: https://img.shields.io/badge/python-3.8%2B-blue.svg
[python-url]: https://www.python.org/downloads/
A Model Context Protocol (MCP) server that provides mathematical calculations and operations using NumPy. This server exposes various mathematical tools through a standardized MCP interface, making it easy to perform numerical computations directly through Claude or other MCP-compatible LLMs.
Features
- Basic arithmetic operations (addition)
- Linear algebra computations (matrix multiplication, eigendecomposition)
- Statistical analysis (mean, median, standard deviation, min, max)
- Polynomial fitting
Installation
Quick Setup with Claude Desktop
The fastest way to get started is to install this server directly in Claude Desktop:
```bash
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