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io.github.daedalus/mcp-numpy

An MCP server that exposes NumPy functionality

Open source Open in the app JSON README (API)

About

An MCP server that exposes NumPy functionality

Details

Kind
MCP servers
Topic
No topic detected
Publisher
daedalus
Origin
official
Category
ferramentas
Transport
local
Version
0.1.0
Last push
2026-04-21T19:27:18Z
Repository state
ativo
Language
Python
License
MIT
Added
2026-08-29 03:02:40
Updated
2026-08-29 03:02:40
Origin id
io.github.daedalus/mcp-numpy

README

# mcp-numpy

> An MCP server that exposes NumPy functionality

[![PyPI](https://img.shields.io/pypi/v/mcp-numpy.svg)](https://pypi.org/project/mcp-numpy/)
[![Python](https://img.shields.io/pypi/pyversions/mcp-numpy.svg)](https://pypi.org/project/mcp-numpy/)
[![Coverage](https://codecov.io/gh/daedalus/mcp-numpy/branch/main/graph/badge.svg)](https://codecov.io/gh/daedalus/mcp-numpy)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

## Install

```bash
pip install mcp-numpy
```

## Usage

### As an MCP Server

To use with Claude Desktop or other MCP clients, add to your `mcp.json`:

```json
{
  "mcpServers": {
    "mcp-numpy": {
      "command": "mcp-numpy"
    }
  }
}
```

### Available Tools

The server exposes the following NumPy functionality as MCP tools:

#### Array Creation
- `np_array` - Create a NumPy array
- `np_zeros` - Create zeros array
- `np_ones` - Create ones array
- `np_full` - Create array filled with value
- `np_arange` - Create array with range
- `np_linspace` - Create evenly spaced array
- `np_eye` - Create identity matrix
- `np_diag` - Create diagonal array

#### Array Manipulation
- `np_reshape` - Reshape array
- `np_transpose` - Transpose array
- `np_concatenate` - Concatenate arrays
- `np_split` - Split array
- `np_tile` - Tile array
- `np_repeat` - Repeat elements
- `np_squeeze` - Remove single-dimensional entries
- `np_flatten` - Flatten array

#### Mathematical Operations
- `np_sum`, `np_mean`, `np_std`, `np_var` - Summary statistics
- `np_min`, `np_max`, `np_argmin`, `np_argmax` - Min/max operations
- `np_dot`, `np_matmul`, `np_cross` - Matrix operations
- `np_trace`, `np_cumsum`, `np_cumprod`, `np_diff` - Array operations

#### Linear Algebra
- `np_inv` - Matrix inverse
- `np_det` - Matrix determinant
- `np_eig` - Eigenvalues and eigenvectors
- `np_svd` - Singular value decomposition
- `np_solve` - Solve linear system
- `np_linalg_norm` - Matrix/vector norm

#### Random
- `np_rand` - Random floats
- `np_randn` - Random normal
- `np_randint` - Random integers
- `np_random_choice` - Random choice
- `np_shuffle` - Shuffle array

#### Statistics
- `np_percentile`, `np_quantile` - Percentiles/quantiles
- `np_histogram` - Histogram
- `np_correlate`, `np_corrcoef` - Correlation

#### Element-wise Math
- `np_add`, `np_subtract`, `np_multiply`, `np_divide` - Arithmetic
- `np_power`, `np_mod` - Power and modulo
- `np_sqrt`, `np_abs` - Basic math
- `np_exp`, `np_log`, `np_log10` - Logarithms
- `np_sin`, `np_cos`, `np_tan` - Trigonometry
- `np_arcsin`, `np_arccos`, `np_arctan` - Inverse trig
- `np_sinh`, `np_cosh`, `np_tanh` - Hyperbolic

#### Array Properties
- `np_shape`, `np_ndim`, `np_size`, `np_dtype` - Properties
- `npastype` - Type conversion

## Development

```bash
git clone https://github.com/daedalus/mcp-numpy.git
cd mcp-numpy
pip install -e ".[test]"

# run tests
pytest

# format
ruff format src/ tests/

# lint
ruff check src/ tests/

# type check
mypy src/
```

mcp-name: io.github.daedalus/mcp-numpy

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