Is io.github.daedalus/mcp-numpy safe to use?

io.github.daedalus/mcp-numpy has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.

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

io.github.daedalus/mcp-numpy supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What can io.github.daedalus/mcp-numpy do?

io.github.daedalus/mcp-numpy provides 72 tools: np_array, np_zeros, np_ones, np_full, np_arange and 67 more. See the full tools list on the server page for descriptions and parameters.

What AI clients work with io.github.daedalus/mcp-numpy?

io.github.daedalus/mcp-numpy is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

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

io.github.daedalus/mcp-numpy is actively maintained — last commit was 27 days ago.

io.github.daedalus/mcp-numpy

mcp-numpy

An MCP server that exposes NumPy functionality

72 tools GitHub PyPI

No known CVEs

No license

Actively maintained

Last commit 27d ago

Works with most clients

Transport: stdio, sse, http

72 tools

Grade F

Edit this pageView history

Data Developer Tools

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

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

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-daedalus-mcp-numpy)](https://mcppedia.org/s/io-github-daedalus-mcp-numpy)

Read me

What io.github.daedalus/mcp-numpy does

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

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

uvx 'mcp-numpy' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

54/100across 5 weighted dimensions

How we score →

0255075100

−46

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked mcp-numpy against OSV.dev.

Inventory

Tools (72)

Click any tool to inspect its schema.

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.daedalus/mcp-numpy safe to use?: io.github.daedalus/mcp-numpy has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install io.github.daedalus/mcp-numpy?: io.github.daedalus/mcp-numpy supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.daedalus/mcp-numpy do?: io.github.daedalus/mcp-numpy provides 72 tools: np_array, np_zeros, np_ones, np_full, np_arange and 67 more. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.daedalus/mcp-numpy?: io.github.daedalus/mcp-numpy is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.daedalus/mcp-numpy actively maintained?: io.github.daedalus/mcp-numpy is actively maintained — last commit was 27 days ago.

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Community

Discussion

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Has anyone used this with Cursor?How do you handle auth?Any alternatives?

Edit this pageView history

Data Developer Tools

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

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

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-daedalus-mcp-numpy)](https://mcppedia.org/s/io-github-daedalus-mcp-numpy)

Read me

What io.github.daedalus/mcp-numpy does

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

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

uvx 'mcp-numpy' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

README

mcp-numpy

An MCP server that exposes NumPy functionality

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

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

54/100across 5 weighted dimensions

How we score →

0255075100

−46

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked mcp-numpy against OSV.dev.

Inventory

Tools (72)

Click any tool to inspect its schema.

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.daedalus/mcp-numpy safe to use?: io.github.daedalus/mcp-numpy has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install io.github.daedalus/mcp-numpy?: io.github.daedalus/mcp-numpy supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.daedalus/mcp-numpy do?: io.github.daedalus/mcp-numpy provides 72 tools: np_array, np_zeros, np_ones, np_full, np_arange and 67 more. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.daedalus/mcp-numpy?: io.github.daedalus/mcp-numpy is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.daedalus/mcp-numpy actively maintained?: io.github.daedalus/mcp-numpy is actively maintained — last commit was 27 days ago.