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Facebook Ads Library MCP Server
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
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.
https://github.com/user-attachments/assets/a47aa689-e89d-4d4b-9df7-6eb3a81937ee
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Hosted Version (Recommended)
**The easiest way to use the Facebook Ads Library MCP is the hosted version from Proxy (useproxy.dev).** No API keys, no Gemini key, no Python, no server to run — just connect and start querying.
- ⚡ **Zero setup** — nothing to install, configure, or maintain
- 🔑 **No API keys** — skip the ScrapeCreators and Gemini keys entirely
- 🔌 **Works everywhere** — ChatGPT, Claude, Cursor, Manus, and anywhere else that supports MCP
- 🚀 **Always up to date** — new tools and fixes ship automatically
👉 **Get started for free at useproxy.dev →**
Prefer to run it yourself? The full self-host setup is documented below.
Hosted vs. Self-Host
| | **Hosted — Proxy (useproxy.dev)** | **Self-Host** |
| --- | --- | --- |
| Setup time | None — connect and go | Python env + config |
| API keys required | None | ScrapeCreators + Gemini |
| Infrastructure | Fully managed | You run and maintain it |
| Updates | Automatic | Manual git pull |
| Works in ChatGPT, Claude, Cursor, Manus | ✅ | ✅ |
| Best for | Most users who just want the data | Developers who want to customize the code |
For most people, the hosted version is the fastest path. Choose self-host if you specifically want to modify or extend the server yourself.
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Example Prompts
Single Brand Analysis
Batch Analysis (New!)
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Installation
Prerequisites
- Python 3.12+
- Anthropic Claude Desktop app (or Cursor)
- Pip (Python package manager), install with python -m pip install
- An API key for an ads data provider, set as SCRAPECREATORS_API_KEY (see configuration below)
- A Google Gemini API key for video analysis (optional, only needed for video ads)
> Prefer not to deal with API keys? See the Hosted Version above to skip setup entirely.
Quick Install (Recommended)
1. **Clone and run the install script**
The install script will:
- Create a virtual environment for dependency isolation
- Install all required dependencies
- Set up your configuration files
2. **Configure your API keys**
Edit the .env file that was created and add your API keys:
- Set your ads data API key as SCRAPECREATORS_API_KEY
- Get your Gemini API key at Google AI Studio (optional, for video analysis)
3. **Follow the displayed MCP configuration**
The install script will show you the exact configuration to add to Claude Desktop or Cursor.
Manual Install
If you prefer to install manually:
1. **Clone this repository**
2. **Create a virtual environment and install dependencies**
3. **Configure API keys**
Copy the template and configure your API keys:
**To obtain API keys:**
- Set your ads data API key as SCRAPECREATORS_API_KEY in the .env file
- Get a Google Gemini API key here (optional, for video analysis)
4. **Connect to the MCP server**
Add the MCP server configuration to your Claude Desktop or Cursor config:
Replace {{PATH_TO_PROJECT}} with the full path to where you cloned this repository.
**Note:** The configuration uses the virtual environment's Python interpreter (venv/bin/python) for better dependency isolation and reliability.
**Note:** API keys are now automatically loaded from the .env file, so you don't need to pass them as command line arguments.