NumPy is the fundamental package for scientific computing with Python. It provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.
Why this server?
Utilizes NumPy as a dependency for working with numerical data in Formula One racing statistics and telemetry analysis.
Why this server?
The MCP server utilizes NumPy for numerical operations in processing weather data.
Why this server?
Stores embedding vectors as NumPy arrays in the Parquet file output
Why this server?
Utilizes NumPy for data analysis operations, enabling statistical calculations and numerical operations on Excel data.
Why this server?
Supports installation and usage of NumPy library in the Python environment as mentioned in the example workflow
Why this server?
Supports installation and usage of NumPy for scientific computing within the sandbox environments.
Why this server?
Used as a dependency for data processing operations in the PBIXRay server, supporting statistical analysis and data manipulation of Power BI models.
Why this server?
Utilizes NumPy for numerical calculations involved in celestial positioning and astronomical computations.
Why this server?
Used for numerical operations in the Python components of DiffuGen
Why this server?
Utilized as a dependency for processing Formula One data, particularly for mathematical operations related to telemetry data analysis.
Why this server?
Supports processing images from numpy arrays, allowing direct integration with numpy-based image processing workflows.
Why this server?
Support for installing and using NumPy in Python containers as demonstrated in examples
Why this server?
Uses NumPy for numerical computations in options analysis, including Greeks calculations and probability estimates
Why this server?
Leverages NumPy for numerical operations in stock data analysis, supporting technical indicators calculation and data processing
Why this server?
Mentioned as an optional dependency that can be included when deploying MCP servers
Why this server?
Used as part of the data processing infrastructure for financial calculations and visualizations
Why this server?
Optional dependency that can be included when running the server to support numerical computing operations when processing Odoo data.
Why this server?
Integrates with NumPy for numerical operations when generating financial charts and data-driven content in PowerPoint presentations.
Why this server?
Uses NumPy for audio processing as part of the speech recognition functionality
Why this server?
Optional dependency that can be specified when starting the MCP server.
Why this server?
The README mentions numpy as an optional dependency that can be specified for deployment and development.
Why this server?
NumPy is listed as a core dependency for the server's technical analysis capabilities.
Why this server?
Exposes NumPy's numerical computation capabilities through an MCP interface, allowing for basic arithmetic, linear algebra operations, statistical analysis, and polynomial fitting
Why this server?
Mentioned as an example package that can be installed and used in the isolated containers for data analysis.