Google Ads Library MCP Server
This is a Model Context Protocol (MCP) server for the Google Ads Transparency Center.
With this you can search Google's public ads transparency center 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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Example Prompts
How many ads is 'AnthropicAI' running? What's their split across video and image?
What messaging is 'AnthropicAI' running right now in their ads?
Analyze the video ads from 'Nike' and extract their visual storytelling strategy, pacing, and brand messaging techniques.
Do a deep comparison to the messaging between 'AnthropicAI', 'Perplexity AI' and 'OpenAI'. Give it a nice forwardable summary.
Installation
Prerequisites
- Python 3.12+
- Anthropic Claude Desktop app (or Cursor)
- Pip (Python package manager), install with
python -m pip install - An access token for Scrape Creators
- A Google Gemini API key for video analysis (optional, only needed for video ads)
Quick Install (Recommended)
-
Clone and run the install script
git clone https://github.com/trypeggy/google-ads-library-mcp.git cd google-ads-library-mcp # For macOS/Linux: ./install.sh # For Windows: install.bat -
Configure your API keys
Edit the
.envfile that was created and add your API keys:- Get your ScrapeCreators API key at scrapecreators.com
- Get your Gemini API key at Google AI Studio (optional, for video analysis)
-
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:
-
Clone this repository
git clone https://github.com/trypeggy/google-ads-library-mcp.git cd google-ads-library-mcp -
Install dependencies
pip install -r requirements.txt -
Configure API keys
Copy the template and configure your API keys:
cp .env.template .env # Then edit .env with your actual API keysTo obtain API keys:
-
Connect to the MCP server
Add the MCP server configuration to your Claude Desktop or Cursor config:
{ "mcpServers": { "google_ad_library": { "command": "/usr/local/opt/python@3.13/bin/python3", "args": [ "{{PATH_TO_PROJECT}}/google-ads-library-mcp/mcp_server.py" ] } } }Replace
{{PATH_TO_PROJECT}}with the full path to where you cloned this repository.Note: API keys are automatically loaded from the
.envfile. Command line arguments are still supported and take priority over environment variables if provided.For Claude Desktop:
Save this as
claude_desktop_config.jsonin your Claude Desktop configuration directory at:~/Library/Application Support/Claude/claude_desktop_config.jsonFor Cursor:
Save this as
mcp.jsonin your Cursor configuration directory at:~/.cursor/mcp.json -
Restart Claude Desktop / Cursor
Open Claude Desktop and you should now see the Google Ads Library as an available integration.
Or restart Cursor.
Technical Details
- Claude sends requests to the Python MCP server
- The MCP server queries the ScrapeCreators API for Google Ads Transparency Center data
- Data flows back through the chain to Claude
Google Ads
This server connects to Google's Ads Transparency Center:
- Google Ads: Uses company domain (e.g., "nike.com") or advertiser ID for search
- Response Format: Returns ads with format types (text/image/video) and detailed variations
- Ad Details: Each ad can have multiple variations with different headlines and descriptions
- Regional Data: Includes region-specific statistics and impression data
Tips:
- Use company domains (e.g., "nike.com") instead of brand names for searching
- Text ads are now supported in addition to image and video ads
- Each ad may have multiple variations with different headlines and descriptions
Available MCP Tools
This MCP server provides tools for interacting with Google Ads Transparency Center objects:
| Tool Name | Description |
|---|---|
get_google_ads | Retrieves currently running ads for a company from Google Ads Transparency Center (by domain or advertiser ID) |
get_google_ad_details | Gets detailed information about a specific Google ad, including all variations and regional stats |
analyze_ad_image | Downloads and analyzes ad images for visual elements, text, colors, and composition |
analyze_ad_video | Downloads and analyzes ad videos using Gemini AI for comprehensive video insights |
get_cache_stats | Gets statistics about cached media (images and videos) and storage usage |
search_cached_media | Searches previously analyzed media by brand, colors, people, or media type |
cleanup_media_cache | Cleans up old cached media files to free disk space |
Troubleshooting
Common Issues
API Key Not Found Error:
- Ensure your
.envfile is in the project root directory - If you don't have a
.envfile, copy it from the template:cp .env.template .env - Check that your API keys are correctly formatted without quotes
- Verify the
.envfile containsSCRAPECREATORS_API_KEY=your_key_here - For video analysis, ensure
GEMINI_API_KEY=your_key_hereis also added
Video Analysis Not Working:
- Confirm you have a valid Google Gemini API key in your
.envfile - Video analysis requires the
GEMINI_API_KEYenvironment variable
MCP Server Connection Issues:
- Verify the path in your MCP configuration points to the correct location
- Make sure you've installed all dependencies with
pip install -r requirements.txt - Restart Claude Desktop/Cursor after configuration changes
For additional Claude Desktop integration troubleshooting, see the MCP documentation. The documentation includes helpful tips for checking logs and resolving common issues.
Google Ads Specific Notes:
- Use company domains (e.g., "nike.com") instead of brand names for searching
- Text ads are now supported in addition to image and video ads
- Each ad may have multiple variations with different headlines and descriptions
Feedback
Your feedback will be massively appreciated. Please tell us which features on that list you like to see next or request entirely new ones.
License
This project is licensed under the MIT License.
