semvec/pypi-packages huggingface dataset:
bfrvc 0.4.2
A Retrieval-based Voice Conversion (RVC) fork
License: MIT
Requires Python: <3.12,>=3.8
Keywords: voice-conversion, audio-processing, rvc, machine-learning

# BF RVC  Fork

___
A simple, high-quality voice conversion tool package..


# Introduction


BFRVC is a powerful voice conversion tool focused on simplicity, quality, and performance. Whether you're an artist, developer, or researcher, BFRVC offers a straightforward platform for high-quality voice transformations.

# Feature


* Easy To Use Inference for RVC.

* Cli Inference for python code alternative

* High quality F0 pitch method, e.g RMVPE, FCPE


# How to install

```
pip install bfrvc -u
```

# How to run

```
bfrvc -h
```


# Note
this for only inference. But to use more feature, get it in [Extension](https://github.com/BF667/BFRVC-Extension.git)
universal-mcp-sharepoint 0.1.2
A Universal MCP Application: universal_mcp_sharepoint
License: MIT
Requires Python: >=3.11

# Sharepoint Universal MCP Server

This repository contains an implementation of an Sharepoint Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Sharepoint's SEO and backlink analysis tools through a unified API.

The server is built using the Universal MCP framework.

This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.

## Usage

You can start using Sharepoint directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Sharepoint.

If you have not used universal mcp before follow the setup instructions at [agentr.dev/quickstart](https://agentr.dev/quickstart)

## Available Tools

The full list of available tools is at [./src/universal_mcp_sharepoint/README.md](./src/universal_mcp_sharepoint/README.md)

## Local Development

### 📋 Prerequisites

Ensure you have the following before you begin:

- **Python 3.11+** (recommended)
- **[uv](https://github.com/astral-sh/uv)** (install globally with `pip install uv`)

### 🛠️ Setup Instructions

Follow the steps below to set up your development environment:

1. **Sync Project Dependencies**

   ```bash
   uv sync
   ```

   This installs all dependencies from `pyproject.toml` into a local virtual environment (`.venv`).

2. **Activate the Virtual Environment**

   For Linux/macOS:

   ```bash
   source .venv/bin/activate
   ```

   For Windows (PowerShell):

   ```powershell
   .venv\Scripts\Activate
   ```

3. **Start the MCP Inspector**

   ```bash
   mcp dev src/universal_mcp_sharepoint/server.py
   ```

   This will start the MCP inspector. Make note of the address and port shown in the console output.

4. **Install the Application**
   ```bash
   mcp install src/universal_mcp_sharepoint/server.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_sharepoint/
│       ├── __init__.py       # Package initializer
│       ├── server.py         # Server entry point
│       ├── app.py            # Application tools
│       └── README.md         # List of application tools
├── tests/                    # Test suite
├── .env                      # Environment variables for local development
├── pyproject.toml            # Project configuration
└── README.md                 # This file
```

## 📄 License

This project is licensed under the [MIT License](LICENSE).

---

_Generated with **MCP CLI** — Happy coding! 🚀_
universal-mcp-aws-s3 0.1.2
A Universal MCP Application: universal_mcp_aws_s3
License: MIT
Requires Python: >=3.11

# Aws-s3 Universal MCP Server

This repository contains an implementation of an Aws-s3 Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Aws-s3's SEO and backlink analysis tools through a unified API.

The server is built using the Universal MCP framework.

This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.

## Usage

You can start using Aws-s3 directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Aws-s3.

If you have not used universal mcp before follow the setup instructions at [agentr.dev/quickstart](https://agentr.dev/quickstart)

## Available Tools

The full list of available tools is at [./src/universal_mcp_aws_s3/README.md](./src/universal_mcp_aws_s3/README.md)

## Local Development

### 📋 Prerequisites

Ensure you have the following before you begin:

- **Python 3.11+** (recommended)
- **[uv](https://github.com/astral-sh/uv)** (install globally with `pip install uv`)

### 🛠️ Setup Instructions

Follow the steps below to set up your development environment:

1. **Sync Project Dependencies**

   ```bash
   uv sync
   ```

   This installs all dependencies from `pyproject.toml` into a local virtual environment (`.venv`).

2. **Activate the Virtual Environment**

   For Linux/macOS:

   ```bash
   source .venv/bin/activate
   ```

   For Windows (PowerShell):

   ```powershell
   .venv\Scripts\Activate
   ```

3. **Start the MCP Inspector**

   ```bash
   mcp dev src/universal_mcp_aws_s3/server.py
   ```

   This will start the MCP inspector. Make note of the address and port shown in the console output.

4. **Install the Application**
   ```bash
   mcp install src/universal_mcp_aws_s3/server.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_aws_s3/
│       ├── __init__.py       # Package initializer
│       ├── server.py         # Server entry point
│       ├── app.py            # Application tools
│       └── README.md         # List of application tools
├── tests/                    # Test suite
├── .env                      # Environment variables for local development
├── pyproject.toml            # Project configuration
└── README.md                 # This file
```

## 📄 License

This project is licensed under the [MIT License](LICENSE).

---

_Generated with **MCP CLI** — Happy coding! 🚀_