Facebook Ads Library Mcp

Abstract

1. Introduction

This is a Model Context Protocol (MCP) server for the Facebook Ads Library.

With this you can search Facebook's public ads library for any company or brand, see what they're currently running and analyze their advertising. You can analyze ad images/text, analyze video ads with comprehensive insights, compare companies' strategies, and get insights into what's working in their campaigns.

Here's an example of what you can do when it's connected to Claude.

2. Objective

MCP Server for Facebook ADs Library - Get instant answers from FB's ad library

This project demonstrates how Python can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

• Claude sends requests to the Python MCP server
• The MCP server intelligently batches and optimizes queries to the ads data API
• Smart caching reduces redundant API calls and improves performance
• Credit monitoring prevents workflow interruption with proactive error handling
• Data flows back through the chain to Claude with enhanced batch information

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/proxy-intell/facebook-ads-library-mcp.git
cd facebook-ads-library-mcp

1. Clone and run the install script
2. Create a virtual environment for dependency isolation
3. Install all required dependencies
4. Set up your configuration files
5. Configure your API keys
6. Set your ads data API key as SCRAPECREATORS_API_KEY
7. Get your Gemini API key at Google AI Studio (optional, for video analysis)
8. Follow the displayed MCP configuration

git clone https://github.com/proxy-intell/facebook-ads-library-mcp.git
   cd facebook-ads-library-mcp

   # For macOS/Linux:
   ./install.sh

   # For Windows:
   install.bat

git clone https://github.com/proxy-intell/facebook-ads-library-mcp.git
   cd facebook-ads-library-mcp

python3 -m venv venv
   ./venv/bin/pip install -r requirements.txt

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by proxy-intell and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.