semvec/pypi-packages huggingface dataset:
universal-mcp-whatsapp 0.1.3
A Universal MCP Application: universal_mcp_whatsapp
License: MIT
Requires Python: >=3.11

# Whatsapp Universal MCP Server

This repository contains an implementation of an Whatsapp Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Whatsapp's tools and services 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 Whatsapp directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Whatsapp.

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 [Tools](./src/universal_mcp_whatsapp/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_whatsapp/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_whatsapp/server.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_whatsapp/
│       ├── __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! 🚀_
unboil-pydantic-sqlalchemy 0.1.2
A library to seamlessly integrate SQLAlchemy models with Pydantic.
License: MIT
Requires Python: >=3.9
Keywords: pydantic, sqlalchemy, unboil


# Pydantic-Alchemy

A SQLAlchemy type decorator for storing and retrieving Pydantic models in PostgreSQL JSONB columns.
This library enables seamless integration between Pydantic and SQLAlchemy, allowing you to store validated data models directly in your database.

## Features
- Store Pydantic models in PostgreSQL JSONB columns
- Automatic validation and serialization/deserialization
- Works with Alembic migrations

## Installation
```bash
pip install pydantic-alchemy
```

## Usage Example
```python
from pydantic import BaseModel
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
from pydantic_alchemy import PydanticJSONB


class Base(DeclarativeBase):
    pass

class Profile(BaseModel):
    age: int
    bio: str


class User(Base):
    __tablename__ = 'users'
    id: Mapped[int] = mapped_column(primary_key=True)
    profile: Mapped[Profile] = mapped_column(PydanticJSONB(Profile))

# Now, assigning a Profile instance to user.profile will automatically validate and serialize it.
```