semvec/pypi-packages huggingface dataset:
cve-mcp-server 0.5.0
A Model Context Protocol server providing tools for CVE vulnerability information queries
Requires Python: >=3.12

# CVE MCP Server

A Model Context Protocol server providing CVE vulnerability information query capabilities. This server enables LLMs to query detailed information for specific CVE IDs, retrieving data from MITRE's CVE database.

### Available Tools

- `query_cve` - Query vulnerability information by CVE ID
  - Required parameters:
    - `cve_id` (string): The CVE identifier (e.g., 'CVE-2021-44228', 'CVE-2023-34362')

## Install
```bash
pip install cve-mcp-server
```

## Configuration
### stdio (default)
```json
{
  "mcpServers": {
    "CVE": {
      "command": "uvx",
      "args": [
        "cve-mcp-server"
      ]
    },
  }
}
```

### SSE
Run SSE Server
```bash
uvx cve-mcp-server sse
```
Use the following configuration to connect directly:
```json
{
    "mcpServers": {
        "amap-mcp-server": {
            "url": "http://localhost:9999"
        }
    }
}
```

## Debugging

You can use the MCP inspector to debug the server:

```bash
npx @modelcontextprotocol/inspector python -m cve-mcp-server
```

## License

cve-mcp-server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
markowitz-portfolio-optimizer 1.27
Optimize you portfolio!
Requires Python: >=3.10

# Portfolio Optimizer

This project implements the simple Markowitz portfolio optimization model.
It is the foundation of modern portfolio theory.

The assumptions of the model are:

1. Risk of a portfolio is based on the variability of returns from said portfolio.
2. An investor is risk averse.
3. An investor prefers to increase consumption.
4. The investor's utility function is concave and increasing, due to their risk aversion and consumption preference.
5. Analysis is based on single period model of investment.
6. An investor either maximizes their portfolio return for a given level of risk or minimizes their risk for a given return.
7. An investor is rational in nature.

More information on theory and calculations can be found on:
https://en.wikipedia.org/wiki/Modern_portfolio_theory

The algorithm needs a timestamped dataset of stock prices,
which can be obtained from Yahoo Finance, Google Finance or other sources.
A sample table structure is as follows:

<div align="center">
<img src="https://github.com/SirArthur100/scientific_python/raw/main/docs/source/images/table.png" width="50%">
</div>

The algorithm will provide the efficient frontier visually:

<div align="center">
<img src="https://github.com/SirArthur100/scientific_python/raw/main/docs/source/images/illustration.png" width="50%">
</div>

and the optimal portfolio weights numerically:

<div align="center">
<img src="https://github.com/SirArthur100/scientific_python/raw/main/docs/source/images/weights.png" width="50%">
</div>

## Requirements
- numpy==1.26.3
- pandas==2.1.4
- matplotlib==3.8.1
- scipy==1.11.4

## Documentation
https://portfolio-optimizer.readthedocs.io/en/latest/

## Source
https://github.com/SirArthur100/scientific_python
idefix-cli 6.0.3
A command line utility belt for Idefix
Requires Python: >=3.10

[![PyPI](https://img.shields.io/pypi/v/idefix_cli.svg?logo=pypi&logoColor=white&label=PyPI)](https://pypi.org/project/idefix-cli/)
[![Documentation Status](https://readthedocs.org/projects/idefix-cli/badge/?version=latest)](https://idefix-cli.readthedocs.io/en/latest/?badge=latest)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/neutrinoceros/idefix_cli/main.svg)](https://results.pre-commit.ci/badge/github/neutrinoceros/idefix_cli/main.svg)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/charliermarsh/ruff)

# `idefix_cli`

`idefix_cli` is a command line utility belt for [Idefix](https://github.com/idefix-code/idefix).

It defines a `idfx` command familly. The builtin command set (`idfx conf`, `idfx run`,
...) can be extended to include arbitrary helper scripts.


## Installation

`idefix_cli` is distributed via the Python Packaging Index (PyPI).

It is recommended to install this tool at the system level, but still in isolation,
using for instance [`uv`](https://docs.astral.sh/uv/) as
```shell
$ uv tool install idefix-cli
```
or [`pipx`](https://pipxproject.github.io/pipx/)
```shell
$ pipx install idefix-cli
```

Otherwise, the most portable way to install the latest stable version is
```shell
$ python -m pip install --user idefix_cli
```

Note that most `idfx` commands explicitly require that the env variable `$IDEFIX_DIR` be
set at runtime.

## Get help

Get a complete description of available commands with
```shell
$ idfx --help
```
Likewise, get help for each command therein as, for instance
```shell
$ idfx run --help
```

For more, read [the documentation !](https://idefix-cli.readthedocs.io/en/latest/?badge=latest)