Enables keyword research and analysis using Google Ads Keyword Planner API, allowing users to discover related keywords and their metrics for SEO optimization
Integrates with Google Cloud Platform for authentication and API access to Google Ads services, requiring a GCP project with Google Ads API enabled
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SEO AI Assistantresearch keywords for 'digital marketing tools'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
App SEO AI
Application for SEO automation and AI-powered optimization with Google Ads Keyword Planner integration.
Features
Keyword research using Google Ads API
SERP analysis
Competitor analysis
SEO recommendations
MCP (Model Context Protocol) integration for AI assistants
Related MCP server: SEO AI Assistant
Prerequisites
Node.js (v14 or higher)
npm or yarn
Google Ads account with API access
Google Cloud Platform project with Google Ads API enabled
Setup
1. Clone the repository
git clone https://github.com/ccnn2509/app-seo-ai.git
cd app-seo-ai2. Install dependencies
npm install3. Configure environment variables
Copy the example environment file:
cp .env.example .envEdit the .env file and fill in your Google Ads API credentials:
# Server Configuration
PORT=3000
NODE_ENV=development
# Google Ads API Configuration
GOOGLE_ADS_DEVELOPER_TOKEN=your_developer_token
GOOGLE_ADS_CLIENT_ID=your_client_id
GOOGLE_ADS_CLIENT_SECRET=your_client_secret
GOOGLE_ADS_REFRESH_TOKEN=your_refresh_token
GOOGLE_ADS_LOGIN_CUSTOMER_ID=your_customer_id_without_dashes
# SERP API Configuration (optional)
SERP_API_KEY=your_serp_api_key4. Get Google Ads API refresh token
Run the following command to get a refresh token:
npm run get-tokenThis will open your browser and guide you through the OAuth2 authentication process. The refresh token will be automatically saved to your .env file.
5. Start the server
For development:
npm run devFor production:
npm startThe server will start on the port specified in your .env file (default: 3000).
API Documentation
API documentation is available at /api-docs when the server is running:
http://localhost:3000/api-docsMCP Integration
This project includes MCP (Model Context Protocol) integration, allowing AI assistants to use the API. The MCP configuration is in the mcp.json file.
To use this with Smithery:
Go to Smithery
Create a new MCP server
Select the
app-seo-airepositoryConfigure the server settings
Deploy the server
Available MCP Tools
research_keywords- Research keywords related to a given topic or seed keywordanalyze_serp- Analyze a SERP (Search Engine Results Page) for a given queryanalyze_competitors- Analyze competitors for a given keyword or domain_health- Health check endpoint
Example Usage
Research Keywords
// Example request to research keywords
fetch('http://localhost:3000/api/keywords/ideas?keyword=seo%20tools&language=en')
.then(response => response.json())
.then(data => console.log(data));Analyze SERP
// Example request to analyze SERP
fetch('http://localhost:3000/api/serp/analyze?query=best%20seo%20tools&location=United%20States')
.then(response => response.json())
.then(data => console.log(data));Analyze Competitors
// Example request to analyze competitors
fetch('http://localhost:3000/api/competitors/analyze?domain=example.com')
.then(response => response.json())
.then(data => console.log(data));License
MIT