semvec/pypi-packages huggingface dataset:
facebook-business-mcp 0.0.9.dev2
unofficial MCP server implementation for Facebook Business API
Requires Python: <4.0,>=3.11

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  <img src="https://raw.githubusercontent.com/promobase/facebook-business-mcp/refs/heads/dev/assets/OpenPromo.svg" alt="OpenPromo Logo" width="340" height="50" />
</div>

---

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[![Python](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/) [![MCP](https://img.shields.io/badge/MCP-Protocol-green)](https://modelcontextprotocol.io/) [![Facebook API](https://img.shields.io/badge/Facebook-Business_API-1877F2?logo=facebook)](https://developers.facebook.com/docs/marketing-apis) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Code style: pyright](https://img.shields.io/badge/code%20style-pyright-000000.svg)](https://github.com/psf/pyright)

</div>

# Facebook Business MCP Server

Unofficial MCP server implementation for [Facebook Business API](https://developers.facebook.com/docs/business-sdk/). You can use this with any clients/LLMs to manage your ad campaigns, ads, etc.

## Features

- **Complete**: implementation is wrapped on top of api specs & python sdk, for full typesafty.
- **MCP Compliant**: Built with [FastMCP](https://gofastmcp.com/getting-started/welcome) for seamless integration with any MCP-compatible client or LLM.
- **Easy Setup**: Simple configuration with environment variables and immediate connectivity to Facebook Business API.

## Installation

### Quick Start

You can run the server directly without installation using `uvx`:

```bash
uvx facebook-business-mcp
```

### Local Installation

```bash
pip install facebook-business-mcp
```

## Setup

1. Set environment variables:

   ```bash
   export FACEBOOK_APP_ID="your-app-id"
   export FACEBOOK_APP_SECRET="your-app-secret"
   export FACEBOOK_ACCESS_TOKEN="your-access-token"
   export FACEBOOK_AD_ACCOUNT_ID="your-ad-account-id"  # optional
   ```

2. Run the server:

   Using uvx (no installation needed):

   ```bash
   uvx facebook-business-mcp
   ```

   Or if installed via pip:

   ```bash
   facebook-business-mcp
   ```

   Or from source:

   ```bash
   uv run main.py
   ```

## License

MIT
OpenRacer 0.6.6
Package to connect with OpenRacer application.
Requires Python: >=3.8

# OpenRacer

## Overview

The OpenRacer WebSocket interface facilitates communication between the Unity-based simulator and Python-based machine learning models. The simulator sends input data for each frame, and the ML model processes it before sending a response back.

This package provides a server interface that manages WebSocket connections and ensures seamless real-time data exchange.

## Installation

```sh
pip install OpenRacer
```

## Usage

### Creating a Custom Model

To integrate an ML model, create a class that **inherits from** `ModelBase` in the OpenRacer package and implement following methonds
* `preProcess` (optional) : used for processing input before passing to `trainEval` or `testEval`
* `trainEval` : will be called each frame for training
* `testEval`: will be called each frame for testing/Race/eval
* `rewardFn`: will be called in each eval to monitor model performance
* `backprop` : will be called for each step in training. Use this to update model based on eval.


```python
from OpenRacer.Model import ModelBase

class MyModel(ModelBase):
    # implement the required functions 
```

### Starting the Interface

The Interface is responsible for handling connections between the simulator and the ML model and Dashboard.

```python
from OpenRacer.Interface import Interface

# Create and start the server
Interface(model=modelInterface).start()
```

### API Reference

Will be updated in some time

### Notes
- Ensure that the **WebSocket server is running before launching the simulator.**

### License

This package is open-source under the MIT License.

### Contributing

Contributions are welcome! Feel free to submit issues or pull requests on GitHub.

### Contact

For questions, reach out to the OpenRacer team via GitHub.
mdnewline 0.1.3
Command line tool to add line breaks after sentences in markdown files for better git diffs
Requires Python: >=3.12

This is a simple command line tool with one purpose: It takes a markdown file that has been written with 
each paragraph on a single line (i.e. no newlines between sentences) and returns a the same file with
newlines added between each sentence.  The use case is when one generates text for uploading to a 
blog site, but then wants the text committed to the repository to have one sentence per line for 
easier diffing.  

This app was generated using Claude Code.  See the CLAUDE.md file for the full generation instructions.