🔥 Facebook Ads Library MCP - Advanced Intelligence Platform

The most powerful Facebook Ads Library MCP server with 15+ advanced tools for competitive intelligence, market analysis, and advertising insights. Built with FastMCP and completely FREE.

🌟 Why This MCP?

Beats paid services like ScrapeCreators ($497/month) with:

• ✅ 15+ Advanced Tools vs their 5-6 basic ones

• ✅ AI-Powered Creative Analysis (they don't have this)

• ✅ ML Performance Prediction (they don't have this)

• ✅ Direct API Access (no proxy limitations)

• ✅ 100% Free & Open Source (vs $497/month)

• ✅ Complete Customization (add your own features)

Related MCP server: Ad Library MCP

🚀 Quick Start

1. Installation

git clone https://github.com/RamsesAguirre777/facebook-ads-library-mcp.git
cd facebook-ads-library-mcp
pip install -r requirements.txt

2. Get Facebook Access Token

1. Go to Facebook Graph API Explorer

2. Generate access token with ads_read permission

3. (Optional) Extend token to 60 days

3. Configure Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "facebook_ads": {
      "command": "python",
      "args": [
        "/path/to/facebook-ads-library-mcp/facebook_ads_mcp_complete.py",
        "--facebook-token",
        "YOUR_FACEBOOK_ACCESS_TOKEN"
      ]
    }
  }
}

4. Restart Claude Desktop

🛠️ 15+ Advanced Tools

🔍 Search & Discovery

• search_facebook_ads() - Advanced search with multiple filters

• discover_competitor_brands() - Find industry competitors automatically

• find_similar_advertisers() - Discover brands with similar strategies

📊 Deep Analysis

• analyze_ad_creative_elements() - AI-powered creative analysis

• analyze_ad_performance_metrics() - Performance insights & KPIs

• analyze_ad_targeting_insights() - Audience targeting analysis

🎯 Monitoring & Tracking

• monitor_brand_ad_changes() - Real-time campaign monitoring

• track_ad_spend_estimation() - Budget tracking & estimation

🏆 Competitive Intelligence

• competitive_ad_analysis() - Multi-brand strategy comparison

• benchmark_against_industry() - Industry benchmarking

• identify_market_opportunities() - Market gap analysis

🔮 Prediction & Optimization

• predict_ad_performance() - ML-powered performance prediction

• generate_facebook_intelligence_report() - Comprehensive reports

🛠️ Utilities

• export_facebook_ads_data() - Export in JSON/CSV/Markdown

💡 Usage Examples

Basic Competitive Analysis

# In Claude Desktop
"Analyze Nike's current Facebook advertising strategy"
"Compare ad strategies between Tesla and BMW"
"Generate a complete intelligence report for Airbnb"

Advanced Market Research

# Discover competitors
"Find all fitness app companies advertising on Facebook"

# Market opportunities
"Identify advertising gaps in the fintech industry"

# Performance prediction
"Predict performance for this ad: 'Get fit in 30 days with our AI trainer'"

Monitoring & Alerts

# Track competitor changes
"Monitor Apple for new ad campaigns and alert me if they launch 5+ new ads"

# Spend tracking
"Estimate Shopify's monthly Facebook ad spend"

🔧 Advanced Configuration

Environment Variables

# Create .env file
echo "FACEBOOK_ACCESS_TOKEN=your_token_here" > .env

Multiple Regions

{
  "mcpServers": {
    "facebook_ads_us": {
      "command": "python",
      "args": ["facebook_ads_mcp_complete.py", "--facebook-token", "US_TOKEN"]
    },
    "facebook_ads_eu": {
      "command": "python", 
      "args": ["facebook_ads_mcp_complete.py", "--facebook-token", "EU_TOKEN"]
    }
  }
}

📈 Performance Comparison

🏗️ Architecture

Facebook Ads Library MCP
├── Core API Wrapper
│   ├── Authentication & Rate Limiting
│   └── Error Handling & Retry Logic
├── Search & Discovery Engine
│   ├── Advanced Filtering
│   └── Competitor Discovery
├── AI Analysis Engine
│   ├── Creative Element Analysis
│   └── Performance Prediction
├── Monitoring System
│   ├── Real-time Change Detection
│   └── Alert System
└── Export & Reporting
    ├── Multiple Format Support
    └── Executive Reports

🔒 Security & Privacy

• No Data Storage - All data processed in real-time

• Direct API Access - No proxy servers or data logging

• Open Source - Complete transparency

• Local Processing - Your data stays on your machine

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

git clone https://github.com/RamsesAguirre777/facebook-ads-library-mcp.git
cd facebook-ads-library-mcp
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements-dev.txt

📖 Documentation

• Setup Guide - Detailed installation instructions

• API Reference - Complete tool documentation

• Examples - Real-world use cases

• Troubleshooting - Common issues & solutions

🔄 Changelog

See CHANGELOG.md for detailed version history.

🆘 Support

• Issues: GitHub Issues

• Discussions: GitHub Discussions

• Email: ramses.aguirre777@email.com

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• FastMCP for the excellent MCP framework

• Crawl4AI for AI-powered web crawling

• Facebook Graph API for providing access to ads data

⭐ Star History