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MCP server · Science

io.github.daedalus/mcp-numpy

· github.com/daedalus/mcp-numpy

An MCP server that exposes NumPy functionality

Unclaimed science
InstallView source
37Low

Scored 6 months ago · breakdown

About io.github.daedalus/mcp-numpy

io.github.daedalus/mcp-numpy is an MCP server in the Science category: an MCP server that exposes NumPy functionality.

Install

uvx
uvx mcp-numpy
pip
pip install mcp-numpy

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (29)

np_arangeCreate array with range

Parameters not published.

np_arrayCreate a NumPy array

Parameters not published.

np_concatenateConcatenate arrays

Parameters not published.

np_detMatrix determinant

Parameters not published.

np_diagCreate diagonal array

Parameters not published.

np_eigEigenvalues and eigenvectors

Parameters not published.

np_eyeCreate identity matrix

Parameters not published.

np_flattenFlatten array

Parameters not published.

np_fullCreate array filled with value

Parameters not published.

np_histogramHistogram

Parameters not published.

Show all 29 tools
np_invMatrix inverse

Parameters not published.

np_linalg_normMatrix/vector norm

Parameters not published.

np_linspaceCreate evenly spaced array

Parameters not published.

np_onesCreate ones array

Parameters not published.

np_randRandom floats

Parameters not published.

np_randintRandom integers

Parameters not published.

np_randnRandom normal

Parameters not published.

np_random_choiceRandom choice

Parameters not published.

np_repeatRepeat elements

Parameters not published.

np_reshapeReshape array

Parameters not published.

np_shuffleShuffle array

Parameters not published.

np_solveSolve linear system

Parameters not published.

np_splitSplit array

Parameters not published.

np_squeezeRemove single-dimensional entries

Parameters not published.

np_svdSingular value decomposition

Parameters not published.

np_tileTile array

Parameters not published.

np_transposeTranspose array

Parameters not published.

np_zerosCreate zeros array

Parameters not published.

npastypeType conversion

Parameters not published.

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README

mcp-numpy

An MCP server that exposes NumPy functionality

PyPI Python Coverage Ruff

Install

pip install mcp-numpy

Usage

As an MCP Server

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

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

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About io.github.daedalus/mcp-numpy

How do I install io.github.daedalus/mcp-numpy?

Run uvx mcp-numpy, then add the server to your MCP client's configuration.

Is io.github.daedalus/mcp-numpy safe to use with an AI agent?

Its trust score is 37 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is io.github.daedalus/mcp-numpy still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.