
SEO Automation and Optimization
Provides SEO automation with tools for keyword research, SERP analysis, and competitor analysis through Google Ads API integration, enabling AI assistants to access these capabilities via MCP.
ccnn2509
README
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
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-ai
2. Install dependencies
npm install
3. Configure environment variables
Copy the example environment file:
cp .env.example .env
Edit 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_key
4. Get Google Ads API refresh token
Run the following command to get a refresh token:
npm run get-token
This 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 dev
For production:
npm start
The 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-docs
MCP 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-ai
repository - Configure 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
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