semvec/pypi-packages huggingface dataset:
sn-api-helper-mcp 0.1.1
MCP server for SignNow API helper tools (stdio only).
License: MIT
Requires Python: >=3.10

[![PyPI](https://img.shields.io/pypi/v/sn-api-helper-mcp)](https://pypi.org/project/sn-api-helper-mcp/)
[![License](https://img.shields.io/github/license/signnow/sn-api-helper-mcp)](https://github.com/signnow/sn-api-helper-mcp/blob/main/LICENSE.md)

# SignNow Api Helper MCP

MCP server for SignNow API helper tools (stdio only).

mcp-name: io.github.signnow/sn-api-helper-mcp

## Installation

```bash
pip install -e .
```

## Run

```bash
python -m sn_api_helper_mcp serve
```

or

```bash
sn-api-helper-mcp serve
```

or

```bash
uvx sn-api-helper-mcp
```

## 🔌 Integrations & Setup

You can use this server with any MCP client. Below are the configurations for the most popular IDEs and apps.

### 1. Claude Desktop

To use SignNow tools directly inside Claude app:

1.  Open your config file:
    * **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
    * **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
2.  Add the following to the `mcpServers` object:

```json
{
  "mcpServers": {
    "signnow-api-helper": {
      "command": "uvx",
      "args": ["sn-api-helper-mcp"]
    }
  }
}

```

3. Restart Claude Desktop.

### 2. Cursor AI

Cursor now supports MCP natively.

1. Open **Cursor Settings** (Cmd/Ctrl + ,).
2. Go to **Features** > **MCP Servers**.
3. Click **+ Add New MCP Server**.
4. Add the following to the `mcpServers` object:

```json
{
  "mcpServers": {
    "signnow-api-helper": {
      "command": "uvx",
      "args": ["sn-api-helper-mcp"]
    }
  }
}

```


### 3. Visual Studio Code (via Cline)

VS Code uses the **Cline** extension (or similar MCP clients) to interact with MCP servers.

1. Install the **Cline** extension from the VS Code Marketplace.
2. Open Cline settings (click the gear icon inside the Cline chat window) -> **MCP Servers**.
3. Add the configuration JSON:

```json
{
  "signnow-api-helper": {
      "command": "uvx",
      "args": ["sn-api-helper-mcp"]
    }
}

```


## Features

- Transport: stdio only
- Tools: `get_signnow_api_info` - Get information about SignNow API
pip-audit-extra 1.0.1
Extended version of pip-audit
License: MIT
Requires Python: <4.0,>=3.9
Keywords: pip-audit, command-line, pip, audit

# pip-audit-extra [![codecov](https://codecov.io/gh/Kirill-Lekhov/pip-audit-extra/graph/badge.svg?token=KBUU5XZ982)](https://codecov.io/gh/Kirill-Lekhov/pip-audit-extra)
Extended version of [pip-audit](https://pypi.org/project/pip-audit/).

## Features
* Viewing vulnerabilities of project dependencies along with severities.

## Installation
```sh
pip install pip-audit-extra
```

## Usage
```sh
cat requirements.txt | pip-audit-extra
```

Poetry
```sh
poetry export -f requirements.txt | pip-audit-extra
# or
poetry run pip-audit-extra --local
```

UV
```sh
uv export --format requirements-txt | pip-audit-extra
# or
uv run pip-audit-extra --local
```

### Severity filter
If necessary, you can filter vulnerabilities by severity.
By default, the filter selects vulnerabilities with the specified severity AND SEVERITIES WITH A HIGHER PRIORITY.
It only affects the vulnerability table.
```sh
cat requirements.txt | pip-audit-extra --severity CRITICAL
```

To select only the specified level, add the prefix `~`, for example:
```sh
cat requirements.txt | pip-audit-extra --severity ~CRITICAL
```

### Fail level
You can set severity of vulnerability from which the audit will be considered to have failed.
```sh
cat requirements.txt | pip-audit-extra --fail-level HIGH
```
In this example, the audit will be considered failed if vulnerabilities of CRITICAL or HIGH severity are found.

### Caching
Caching is used to speed up re-auditing by maintaining the severity of vulnerabilities.

By default, cached record is valid for a day from the moment of saving.
You can control the lifetime of entries in the cache.

```sh
# (default) 1 day
cat requirements.txt | pip-audit-extra --cache-lifetime 1d

# disable cache
cat requirements.txt | pip-audit-extra --cache-lifetime 0

# 1 minute
cat requirements.txt | pip-audit-extra --cache-lifetime 60

# 1 weak
cat requirements.txt | pip-audit-extra --cache-lifetime 604800

# 15 seconds
cat requirements.txt | pip-audit-extra --cache-lifetime 15s

# 30 minutes
cat requirements.txt | pip-audit-extra --cache-lifetime 30m

# 12 hours
cat requirements.txt | pip-audit-extra --cache-lifetime 12h

# 1 weak
cat requirements.txt | pip-audit-extra --cache-lifetime 7d
```

#### Custom cache path
You can use the `PAE_CACHE_DIR` environment variable to specify path to the cache folder.

```sh
PAE_CACHE_DIR="/tmp/pae/" pip-audit-extra --local
```

### Local packages check
You can check packages which installed in the current local environment without installing dependencies in isolated environment.

```sh
pip-audit-extra --local
```

### Disable pip
You can skip isolated environment building (only if requirements.txt file contains hashes) to speedup audit.

```sh
cat requirements.txt | pip-audit-extra --disable-pip
```

#### ⛔Limitations⛔
There are certain types of dependencies that are not supported by pip-audit
(for example, dependencies installed directly from github with a specific hash).
d2spy 0.4.2
Python package for interacting with a Data to Science instance.
License: MIT
Requires Python: <4.0,>=3.9
Keywords: python, data to science, uas

# Welcome to Data to Science Python (d2spy)

[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gdslab/d2spy/blob/master)
[![Jupyter Notebook](https://img.shields.io/badge/Open%20in%20JuypterHub%20-%20%233776AB?logo=jupyter&logoColor=%23F37626&labelColor=%23F5F5F5)](https://lab.d2s.org)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

<p align="center">
  <img
    src="https://py.d2s.org/assets/d2s-logo.png"
    alt="Data to Science logo"
    width="128"
  >
</p>

D2spy is a Python package for interacting with Data to Science instances.

## Installation

Install the core package with minimal dependencies:

```bash
pip install d2spy
```

Or install with geospatial features for raster clipping and EXIF extraction:

```bash
pip install d2spy[geo]
```

### What's the difference?

**Core installation (`d2spy`):**
- Requires only `requests` library
- Full API access: authentication, projects, flights, data uploads
- Server-side analysis: NDVI, ExG, zonal statistics (job submission)
- Perfect for: lightweight integrations, CI/CD pipelines, QGIS plugins (which already include geo libraries)

**Geo installation (`d2spy[geo]`):**
- Adds `rasterio`, `geopandas`, and `exifread` libraries
- Client-side geospatial processing: raster clipping, EXIF data extraction, bounding box generation
- Required for: `DataProduct.clip()`, `get_exif_data()`, `get_bounding_box_from_exif_data()`

### Bundling with QGIS Plugins

If you're bundling d2spy in a QGIS plugin, extract the wheel and copy the `d2spy` folder into your plugin directory. Since QGIS already includes most geospatial libraries, geo features will work automatically without needing to install `d2spy[geo]`.

## Features

### Core Features (available with base installation)
- Sign in to your Data to Science instance
- Access your projects, flights, and data products
- Create new projects and flights
- Upload data products to flights (rasters, point clouds, raw data)
- Server-side analysis: NDVI, ExG, zonal statistics

### Geospatial Features (requires `d2spy[geo]`)
- Client-side raster clipping by polygon
- Extract EXIF data from images
- Generate bounding boxes from image collections

## Documentation

- [Homepage](https://py.d2s.org/)
- [Guides](https://py.d2s.org/guides)
- [API Reference](https://py.d2s.org/api_client/)